From 4363c1814e828f30da3a1461f84d386ae1e202b5 Mon Sep 17 00:00:00 2001 From: Brantly Callaway Date: Fri, 31 Jan 2025 10:25:32 -0500 Subject: [PATCH] add website, update citation workflow --- .github/workflows/update-citation-cff.yaml | 55 --- .github/workflows/update-citation.yml | 43 +++ DESCRIPTION | 4 +- NAMESPACE | 2 + R/classes.R | 16 +- R/process_dose_gt.R | 99 +++++ README.Rmd | 116 +++--- README.md | 311 ++++++++++------ TODO | 6 +- docs/404.html | 27 +- docs/apple-touch-icon.png | Bin 0 -> 10412 bytes docs/authors.html | 36 +- docs/favicon-96x96.png | Bin 0 -> 4181 bytes docs/favicon.ico | Bin 0 -> 15086 bytes docs/favicon.svg | 3 + docs/index.html | 341 ++++++++++++------ docs/logo.png | Bin 0 -> 21499 bytes docs/pkgdown.yml | 7 +- docs/reference/aggte_obj.html | 144 ++++++++ docs/reference/attgt_if.html | 32 +- docs/reference/attgt_noif.html | 30 +- docs/reference/attgt_pte_aggregations.html | 30 +- docs/reference/compute.pte.html | 32 +- docs/reference/compute.pte2.html | 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insertions(+), 1048 deletions(-) delete mode 100644 .github/workflows/update-citation-cff.yaml create mode 100644 .github/workflows/update-citation.yml create mode 100644 docs/apple-touch-icon.png create mode 100644 docs/favicon-96x96.png create mode 100644 docs/favicon.ico create mode 100644 docs/favicon.svg create mode 100644 docs/logo.png create mode 100644 docs/reference/aggte_obj.html create mode 100644 docs/reference/crit_val_checks.html create mode 100644 docs/reference/dose_obj.html create mode 100644 docs/reference/figures/logo.png create mode 100644 docs/reference/getSE.html create mode 100644 docs/reference/get_agg_inf_func.html create mode 100644 docs/reference/ggpte_cont.html create mode 100644 docs/reference/keep_all_pretreatment_subset.html create mode 100644 docs/reference/keep_all_untreated_subset.html create mode 100644 docs/reference/overall_weights.html create mode 100644 docs/reference/print.summary.dose_obj.html create mode 100644 docs/reference/pte_dose_results.html create mode 100644 docs/reference/summary.aggte_obj.html create mode 100644 docs/reference/summary.dose_obj.html create mode 100644 docs/reference/wif.html create mode 100644 docs/site.webmanifest create mode 100644 docs/web-app-manifest-192x192.png create mode 100644 docs/web-app-manifest-512x512.png create mode 100644 inst/.CITATION.swp create mode 100644 inst/CITATION create mode 100644 man/print.summary.dose_obj.Rd create mode 100644 man/summary.dose_obj.Rd create mode 100644 pkgdown/favicon/apple-touch-icon.png create mode 100644 pkgdown/favicon/favicon-96x96.png create mode 100644 pkgdown/favicon/favicon.ico create mode 100644 pkgdown/favicon/favicon.svg create mode 100644 pkgdown/favicon/site.webmanifest create mode 100644 pkgdown/favicon/web-app-manifest-192x192.png create mode 100644 pkgdown/favicon/web-app-manifest-512x512.png diff --git a/.github/workflows/update-citation-cff.yaml b/.github/workflows/update-citation-cff.yaml deleted file mode 100644 index 4937d5d..0000000 --- a/.github/workflows/update-citation-cff.yaml +++ /dev/null @@ -1,55 +0,0 @@ -# Workflow derived from https://github.com/r-lib/actions/tree/master/examples -# The action runs when: -# - A new release is published -# - The DESCRIPTION or inst/CITATION are modified -# - Can be run manually -# For customizing the triggers, visit https://docs.github.com/en/actions/learn-github-actions/events-that-trigger-workflows -on: - release: - types: [published] - push: - branches: [master, main] - paths: - - DESCRIPTION - - inst/CITATION - workflow_dispatch: - -name: Update CITATION.cff - -jobs: - update-citation-cff: - runs-on: macos-latest - env: - GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }} - steps: - - uses: actions/checkout@v2 - - uses: r-lib/actions/setup-r@v2 - - uses: r-lib/actions/setup-r-dependencies@v2 - with: - extra-packages: | - any::cffr - any::V8 - - - name: Update CITATION.cff - run: | - - library(cffr) - - # Customize with your own code - # See https://docs.ropensci.org/cffr/articles/cffr.html - - # Write your own keys - mykeys <- list() - - # Create your CITATION.cff file - cff_write(keys = mykeys) - - shell: Rscript {0} - - - name: Commit results - run: | - git config --local user.name "$GITHUB_ACTOR" - git config --local user.email "$GITHUB_ACTOR@users.noreply.github.com" - git add CITATION.cff - git commit -m 'Update CITATION.cff' || echo "No changes to commit" - git push origin || echo "No changes to commit" diff --git a/.github/workflows/update-citation.yml b/.github/workflows/update-citation.yml new file mode 100644 index 0000000..cca7c8e --- /dev/null +++ b/.github/workflows/update-citation.yml @@ -0,0 +1,43 @@ +name: Update Citation Files + +on: + push: + paths: + - "DESCRIPTION" + workflow_dispatch: + +jobs: + update-citation: + runs-on: ubuntu-latest + + steps: + - name: Check out repository + uses: actions/checkout@v4 + + - name: Set up R + uses: r-lib/actions/setup-r@v2 + + - name: Install dependencies + run: | + Rscript -e 'install.packages(c("usethis", "cffr", "desc"))' + + - name: Update inst/CITATION + run: | + Rscript -e ' + library(desc); + d <- desc::desc_get(); + citation_text <- sprintf("citHeader(\"To cite this package, use:\")\n\nbibentry(\n bibtype = \"Manual\",\n title = \"%s\",\n author = %s,\n year = \"%s\",\n note = \"R package version %s\",\n url = \"%s\"\n)", + d["Title"], d["Authors@R"], format(Sys.Date(), "%Y"), d["Version"], d["URL"]); + writeLines(citation_text, "inst/CITATION")' + + - name: Update CITATION.cff + run: | + Rscript -e 'cffr::cff_write()' + + - name: Commit and Push if Changed + run: | + git config --global user.name "github-actions" + git config --global user.email "github-actions@github.com" + git add inst/CITATION CITATION.cff + git commit -m "Auto-update citation files" || echo "No changes to commit" + git push diff --git a/DESCRIPTION b/DESCRIPTION index d9b4d2f..33195cf 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,12 +1,12 @@ Package: ptetools Title: Panel Treatment Effects Tools -Version: 0.0.1 +Version: 1.0.0 Authors@R: person(given = "Brantly", family = "Callaway", role = c("aut", "cre"), email = "brantly.callaway@uga.edu") -URL: https://github.com/bcallaway11/pte +URL: https://github.com/bcallaway11/ptetools Description: This is fairly generic code for estimating treatment effects with panel data. This is useful code in my own work and will perhaps be useful to others. It builds heavily on the \code{did} package. In particular, it breaks into separate steps organizing the data, looping over groups and time periods, computing group-time average treatment effects, and aggregating group-time average treatment effects. Often, one is able to implement a new identification/estimation procedure by simply replacing the step on estimating group-time average treatment effects. See several different examples of this approach in the README. License: GPL-3 Encoding: UTF-8 diff --git a/NAMESPACE b/NAMESPACE index faa1358..bbcf312 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -2,8 +2,10 @@ S3method(print,group_time_att) S3method(print,pte_results) +S3method(print,summary.dose_obj) S3method(print,summary.pte_results) S3method(summary,aggte_obj) +S3method(summary,dose_obj) S3method(summary,group_time_att) S3method(summary,pte_emp_boot) S3method(summary,pte_results) diff --git a/R/classes.R b/R/classes.R index c8ba572..e2783a5 100644 --- a/R/classes.R +++ b/R/classes.R @@ -210,12 +210,15 @@ summary.pte_results <- function(object, ...) { c1name <- "Event Time" colnames(out2) <- c(c1name, "Estimate", "Std. Error", cband_text1, "Conf. Band]", "") + target_parameter <- object$ptep$target_parameter + out <- list( overall_att = out1, event_study = out2, alp = alp, bstrap = bstrap, - cband = cband + cband = cband, + target_parameter = target_parameter ) class(out) <- "summary.pte_results" @@ -252,10 +255,19 @@ print.summary.pte_results <- function(x, ...) { out1 <- object$overall_att out2 <- object$event_study alp <- object$alp + target_parameter <- object$target_parameter + + # in a handful of cases, the overall parameter is not an ATT + # (e.g., it could be an ACRT with a continuous treatment), + # allow for possibility of difference here: + att_text <- "Overall ATT" # default + if (isTRUE(target_parameter == "slope")) { + att_text <- "Overall ACRT" + } # overall att cat("\n") - cat("Overall ATT: \n") + cat(paste0(att_text, ": \n")) colnames(out1) <- c("ATT", " Std. Error", paste0(" [ ", 100 * (1 - alp), "% "), "Conf. Int.]", "") print(out1, row.names = FALSE) cat("\n\n") diff --git a/R/process_dose_gt.R b/R/process_dose_gt.R index b2fba98..28ca56e 100644 --- a/R/process_dose_gt.R +++ b/R/process_dose_gt.R @@ -163,3 +163,102 @@ dose_obj <- function( out } + +#' @title summary.dose_obj +#' +#' @description summarizes a `dose_obj` object +#' +#' @param object an `dose_obj` object +#' @param ... extra arguments +#' +#' @export +summary.dose_obj <- function(object, ...) { + dose_obj <- object + out <- list( + overall_att = dose_obj$overall_att, + overall_att_se = dose_obj$overall_att_se, + overall_acrt = dose_obj$overall_acrt, + overall_acrt_se = dose_obj$overall_acrt_se, + dose = dose_obj$dose, + att.d = dose_obj$att.d, + att.d_se = dose_obj$att.d_se, + att.d_crit.val = dose_obj$att.d_crit.val, + acrt.d = dose_obj$acrt.d, + acrt.d_se = dose_obj$acrt.d_se, + acrt.d_crit.val = dose_obj$acrt.d_crit.val, + alp = dose_obj$pte_params$alp, + cband = dose_obj$pte_params$cband, + bstrap = dose_obj$pte_params$bstrap + ) + class(out) <- "summary.dose_obj" + out +} + +#' @title print.summary.dose_obj +#' +#' @description prints a summary of a `dose_obj` object +#' +#' @param x a list containing the summary of a `dose_obj` object +#' @param ... extra arguments +#' +#' @export +print.summary.dose_obj <- function(x, ...) { + # browser() + alp <- x$alp + cband <- x$cband + bstrap <- TRUE # TODO: hardcoded because this only option + + # ATT(d) + cat("ATT(d):\n") + + cband_text1a <- paste0(100 * (1 - alp), "% ") + cband_text1b <- ifelse(bstrap, + ifelse(cband, "Simult. ", "Pointwise "), + "Pointwise " + ) + cband_text1 <- paste0("[", cband_text1a, cband_text1b) + + cband_lower <- x$att.d - x$att.d_crit.val * x$att.d_se + cband_upper <- x$att.d + x$att.d_crit.val * x$att.d_se + + sig <- (cband_upper < 0) | (cband_lower > 0) + sig[is.na(sig)] <- FALSE + sig_text <- ifelse(sig, "*", "") + + out <- cbind.data.frame(x$dose, x$att.d, x$att.d_se, cband_lower, cband_upper) + out <- round(out, 4) + out <- cbind.data.frame(out, sig_text) + + + colnames(out) <- c("dose", "ATT(d)", "Std. Error", cband_text1, "Conf. Band]", "") + print(out, row.names = FALSE, justify = "centre") + cat("\n\n") + + # ATT(d) + cat("ACRT(d):\n") + + cband_text1a <- paste0(100 * (1 - alp), "% ") + cband_text1b <- ifelse(bstrap, + ifelse(cband, "Simult. ", "Pointwise "), + "Pointwise " + ) + cband_text1 <- paste0("[", cband_text1a, cband_text1b) + + cband_lower <- x$acrt.d - x$acrt.d_crit.val * x$acrt.d_se + cband_upper <- x$acrt.d + x$acrt.d_crit.val * x$acrt.d_se + + sig <- (cband_upper < 0) | (cband_lower > 0) + sig[is.na(sig)] <- FALSE + sig_text <- ifelse(sig, "*", "") + + out <- cbind.data.frame(x$dose, x$acrt.d, x$acrt.d_se, cband_lower, cband_upper) + out <- round(out, 4) + out <- cbind.data.frame(out, sig_text) + + + colnames(out) <- c("dose", "ACRT(d)", "Std. Error", cband_text1, "Conf. Band]", "") + print(out, row.names = FALSE, justify = "centre") + cat("---\n") + cat("Signif. codes: `*' confidence band does not cover 0") + cat("\n\n") +} diff --git a/README.Rmd b/README.Rmd index 7e43ef4..123f3a3 100644 --- a/README.Rmd +++ b/README.Rmd @@ -13,25 +13,25 @@ knitr::opts_chunk$set( ``` ```{r, echo=FALSE, results="hide", warning=FALSE, message=FALSE} -devtools::load_all("~/Dropbox/pte") +devtools::load_all("~/Dropbox/ptetools") devtools::load_all("~/Dropbox/ppe") load("~/Dropbox/ppe/data/covid_data.rda") library(ggplot2) library(dplyr) ``` -# Panel Treatment Effects (pte) Package pte +# Panel Treatment Effects Tools (ptetools) Package ptetools -The `pte` package compartmentalizes the steps needed to implement estimators of group-time average treatment effects (and their aggregations) in order to make it easier to apply the same sorts of arguments outside of their "birthplace" in the literature on difference-in-differences. +The `ptetools` package compartmentalizes the steps needed to implement estimators of group-time average treatment effects (and their aggregations) in order to make it easier to apply the same sorts of arguments outside of their "birthplace" in the literature on difference-in-differences. This code is lightweight, only works for balanced panels, and has minimal error checking. That said, it should be useful projects that build on top of group-time average treatment effects in order to deliver estimates of causal effects in panel data settings. -The main function is called `pte`. The most important paramters that it takes in are `subset_fun` and `attgt_fun`. These are functions that the user should pass to `pte`. +The main function is called `pte`. The most important paramters that it takes in are `subset_fun` and `attgt_fun`. These are functions that the user should pass to `pte`. -`subset_fun` takes in the overall data, a group, a time period, and possibly other arguments and returns a `data.frame` containing the relevant subset of the data, an outcome, and whether or not a unit should be considered to be in the treated or comparison group for that group/time. There is one example of a relevant subset function provided in the package: [the `two_by_two_subset` function](https://github.com/bcallaway11/pte/blob/master/R/subset_functions.R). This function takes an original dataset, subsets it into pre- and post-treatment periods and denotes treated and untreated units. This particular subset is perhaps the most common/important one for thinking about treatment effects with panel data. +`subset_fun` takes in the overall data, a group, a time period, and possibly other arguments and returns a `data.frame` containing the relevant subset of the data, an outcome, and whether or not a unit should be considered to be in the treated or comparison group for that group/time. There is one example of a relevant subset function provided in the package: [the `two_by_two_subset` function](https://github.com/bcallaway11/ptetools/blob/master/R/subset_functions.R). This function takes an original dataset, subsets it into pre- and post-treatment periods and denotes treated and untreated units. This particular subset is perhaps the most common/important one for thinking about treatment effects with panel data. -The other main function is `attgt_fun`. This function should be able to take in the correct subset of data, possibly along with other arguments to the function, and report an *ATT* for that subset. With minor modification, this function should be availble for most any sort of treatment effects application --- for example, if you can solve the baseline 2x2 case in difference in differences, you should use that function here, and the `pte` package will take care of dealing with the variation in treatment timing. +The other main function is `attgt_fun`. This function should be able to take in the correct subset of data, possibly along with other arguments to the function, and report an *ATT* for that subset. With minor modification, this function should be availble for most any sort of treatment effects application --- for example, if you can solve the baseline 2x2 case in difference in differences, you should use that function here, and the `ptetools` package will take care of dealing with the variation in treatment timing. -If `attgt_fun` returns an influence function, then the `pte` package will also conduct inference using the multiplier bootstrap (which is fast) and produce uniform confidence bands (which adjust for multiple testing). +If `attgt_fun` returns an influence function, then the `ptetools` package will also conduct inference using the multiplier bootstrap (which is fast) and produce uniform confidence bands (which adjust for multiple testing). The default output of `pte` is an overall treatment effect on the treated (i.e., across all groups that participate in the treatment in any time period) and dynamic effects (i.e., event studies). More aggregations are possible, but these seem to be the leading cases; aggregations of group-time average treatment effects are discussed at length in [Callaway and Sant'Anna (2021)](https://doi.org/10.1016/j.jeconom.2020.12.001). @@ -39,36 +39,38 @@ Here are a few examples: ## Example 1: Difference in differences -The [`did` package](https://bcallaway11.github.io/did/), which is based on [Callaway and Sant'Anna (2021)](https://doi.org/10.1016/j.jeconom.2020.12.001), includes estimates of group-time average treatment effects, *ATT(g,t)*, based on a difference in differences identification strategy. The following example demonstrates that it is easy to compute group-time average treatment effects using difference in differences using the `pte` package. [*Note:* This is definitely not the recommended way of doing this as there is very little error handling, etc. here, but it is rather a proof of concept. You should use the `did` package for this case.] +The [`did` package](https://bcallaway11.github.io/did/), which is based on [Callaway and Sant'Anna (2021)](https://doi.org/10.1016/j.jeconom.2020.12.001), includes estimates of group-time average treatment effects, *ATT(g,t)*, based on a difference in differences identification strategy. The following example demonstrates that it is easy to compute group-time average treatment effects using difference in differences using the `ptetools` package. [*Note:* This is definitely not the recommended way of doing this as there is very little error handling, etc. here, but it is rather a proof of concept. You should use the `did` package for this case.] This example reproduces DID estimates of the effect of the minimum wage on employment using data from the `did` package. ```{r} library(did) data(mpdta) -did_res <- pte(yname="lemp", - gname="first.treat", - tname="year", - idname="countyreal", - data=mpdta, - setup_pte_fun=setup_pte, - subset_fun=two_by_two_subset, - attgt_fun=did_attgt, - xformla=~lpop) +did_res <- pte( + yname = "lemp", + gname = "first.treat", + tname = "year", + idname = "countyreal", + data = mpdta, + setup_pte_fun = setup_pte, + subset_fun = two_by_two_subset, + attgt_fun = did_attgt, + xformla = ~lpop +) summary(did_res) ggpte(did_res) ``` -What's most interesting here, is that the only "new" code that needs to be writte is in [the `did_attgt` function](https://github.com/bcallaway11/pte/blob/master/R/attgt_functions.R). You will see that this is a very small amount of code. +What's most interesting here, is that the only "new" code that needs to be writte is in [the `did_attgt` function](https://github.com/bcallaway11/ptetools/blob/master/R/attgt_functions.R). You will see that this is a very small amount of code. ## Example 2: Policy Evaluation during a Pandemic As a next example, consider trying to estimate effects of Covid-19 related policies during a pandemic. The estimates below are for the effects of state-leve shelter-in-place orders during the early part of the pandemic. -[Callaway and Li (2021)](https://arxiv.org/abs/2105.06927) argue that a particular unconfoundedness-type strategy is more appropriate in this context than DID-type strategies due to the spread of Covid-19 cases being highly nonlinear. However, they still deal with the challenge of variation in treatment timing. Therefore, it is still useful to think about group-time average treatment effects, but the DID strategy should be replaced with their particular unconfoundedness type assumption. +[Callaway and Li (2021)](https://arxiv.org/abs/2105.06927) argue that a particular unconfoundedness-type strategy is more appropriate in this context than DID-type strategies due to the spread of Covid-19 cases being highly nonlinear. However, they still deal with the challenge of variation in treatment timing. Therefore, it is still useful to think about group-time average treatment effects, but the DID strategy should be replaced with their particular unconfoundedness type assumption. -The `pte` package is particularly useful here. +The `ptetools` package is particularly useful here. ```{r} # formula for covariates @@ -77,15 +79,16 @@ xformla <- ~ current + I(current^2) + region + totalTestResults ```{r echo=FALSE, results=FALSE, warning=FALSE} # drop some data as in paper -trim_id_list <- lapply(c(10,15,20,25,30), - did::trimmer, - tname="time.period", - idname="state_id", - gname="group", - xformla=xformla, - data=covid_data, - control_group="nevertreated", - threshold=0.95) +trim_id_list <- lapply(c(10, 15, 20, 25, 30), + did::trimmer, + tname = "time.period", + idname = "state_id", + gname = "group", + xformla = xformla, + data = covid_data, + control_group = "nevertreated", + threshold = 0.95 +) time_id_list <- unlist(trim_id_list) # unique(subset(covid_data, state_id %in% time_id_list)$state) @@ -94,36 +97,37 @@ covid_data2 <- subset(covid_data, !(state_id %in% time_id_list)) ```{r} -covid_res <- pte(yname="positive", - gname="group", - tname="time.period", - idname="state_id", - data=covid_data2, - setup_pte_fun=setup_pte_basic, - subset_fun=two_by_two_subset, - attgt_fun=covid_attgt, - xformla=xformla, - max_e=21, - min_e=-10) +covid_res <- pte( + yname = "positive", + gname = "group", + tname = "time.period", + idname = "state_id", + data = covid_data2, + setup_pte_fun = setup_pte_basic, + subset_fun = two_by_two_subset, + attgt_fun = covid_attgt, + xformla = xformla, + max_e = 21, + min_e = -10 +) summary(covid_res) -ggpte(covid_res) + ylim(c(-1000,1000)) +ggpte(covid_res) + ylim(c(-1000, 1000)) ``` -What's most interesting is just how little code needs to be written here. The only new code required is the `ppe::covid_attgt` function which is [available here](https://github.com/bcallaway11/ppe/blob/master/R/covid_attgt.R), and, as you can see, this is very simple. +What's most interesting is just how little code needs to be written here. The only new code required is the `ppe::covid_attgt` function which is [available here](https://github.com/bcallaway11/ppe/blob/master/R/covid_attgt.R), and, as you can see, this is very simple. ## Example 3: Empirical Bootstrap -The code above used the multiplier bootstrap. The great thing about the multiplier bootstrap is that it's fast. But in order to use it, you have to work out the influence function for the estimator of *ATT(g,t)*. Although I pretty much always end up doing this, it can be tedious, and it can be nice to get a working version of the code for a project going before working out the details on the influence function. +The code above used the multiplier bootstrap. The great thing about the multiplier bootstrap is that it's fast. But in order to use it, you have to work out the influence function for the estimator of *ATT(g,t)*. Although I pretty much always end up doing this, it can be tedious, and it can be nice to get a working version of the code for a project going before working out the details on the influence function. -The `pte` package can be used with the empirical bootstrap. There are a few limitations. First, it's going to be substantially slower. Second, this code just reports pointwise confidence intervals. However, this basically is set up to fit into my typical workflow, and I see this as a way to get preliminary results. +The `ptetools` package can be used with the empirical bootstrap. There are a few limitations. First, it's going to be substantially slower. Second, this code just reports pointwise confidence intervals. However, this basically is set up to fit into my typical workflow, and I see this as a way to get preliminary results. Let's demonstrate it. To do this, consider the same setup as in Example 1, but where no influence function is returned. Let's write the code for this: ```{r} # did with no influence function did_attgt_noif <- function(gt_data, xformla, ...) { - # call original function did_gt <- did_attgt(gt_data, xformla, ...) @@ -136,18 +140,20 @@ did_attgt_noif <- function(gt_data, xformla, ...) { Now, we can show the same sorts of results as above ```{r} -did_res_noif <- pte(yname="lemp", - gname="first.treat", - tname="year", - idname="countyreal", - data=mpdta, - setup_pte_fun=setup_pte, - subset_fun=two_by_two_subset, - attgt_fun=did_attgt_noif, #this is only diff. - xformla=~lpop) +did_res_noif <- pte( + yname = "lemp", + gname = "first.treat", + tname = "year", + idname = "countyreal", + data = mpdta, + setup_pte_fun = setup_pte, + subset_fun = two_by_two_subset, + attgt_fun = did_attgt_noif, # this is only diff. + xformla = ~lpop +) summary(did_res_noif) ggpte(did_res_noif) ``` -What's exciting about this is just how little new code needs to be written. +What's exciting about this is just how little new code needs to be written. diff --git a/README.md b/README.md index 0f3a3e6..4c3500d 100644 --- a/README.md +++ b/README.md @@ -1,9 +1,9 @@ -# Panel Treatment Effects (pte) Package pte +# Panel Treatment Effects Tools (ptetools) Package ptetools -The `pte` package compartmentalizes the steps needed to implement +The `ptetools` package compartmentalizes the steps needed to implement estimators of group-time average treatment effects (and their aggregations) in order to make it easier to apply the same sorts of arguments outside of their “birthplace” in the literature on @@ -24,7 +24,7 @@ relevant subset of the data, an outcome, and whether or not a unit should be considered to be in the treated or comparison group for that group/time. There is one example of a relevant subset function provided in the package: [the `two_by_two_subset` -function](https://github.com/bcallaway11/pte/blob/master/R/subset_functions.R). +function](https://github.com/bcallaway11/ptetools/blob/master/R/subset_functions.R). This function takes an original dataset, subsets it into pre- and post-treatment periods and denotes treated and untreated units. This particular subset is perhaps the most common/important one for thinking @@ -36,13 +36,13 @@ to the function, and report an *ATT* for that subset. With minor modification, this function should be availble for most any sort of treatment effects application — for example, if you can solve the baseline 2x2 case in difference in differences, you should use that -function here, and the `pte` package will take care of dealing with the -variation in treatment timing. +function here, and the `ptetools` package will take care of dealing with +the variation in treatment timing. -If `attgt_fun` returns an influence function, then the `pte` package -will also conduct inference using the multiplier bootstrap (which is -fast) and produce uniform confidence bands (which adjust for multiple -testing). +If `attgt_fun` returns an influence function, then the `ptetools` +package will also conduct inference using the multiplier bootstrap +(which is fast) and produce uniform confidence bands (which adjust for +multiple testing). The default output of `pte` is an overall treatment effect on the treated (i.e., across all groups that participate in the treatment in @@ -62,7 +62,7 @@ on [Callaway and Sant’Anna estimates of group-time average treatment effects, *ATT(g,t)*, based on a difference in differences identification strategy. The following example demonstrates that it is easy to compute group-time average -treatment effects using difference in differences using the `pte` +treatment effects using difference in differences using the `ptetools` package. \[*Note:* This is definitely not the recommended way of doing this as there is very little error handling, etc. here, but it is rather a proof of concept. You should use the `did` package for this case.\] @@ -73,35 +73,61 @@ on employment using data from the `did` package. ``` r library(did) data(mpdta) -did_res <- pte(yname="lemp", - gname="first.treat", - tname="year", - idname="countyreal", - data=mpdta, - setup_pte_fun=setup_pte, - subset_fun=two_by_two_subset, - attgt_fun=did_attgt, - xformla=~lpop) +did_res <- pte( + yname = "lemp", + gname = "first.treat", + tname = "year", + idname = "countyreal", + data = mpdta, + setup_pte_fun = setup_pte, + subset_fun = two_by_two_subset, + attgt_fun = did_attgt, + xformla = ~lpop +) #> Warning in pte(yname = "lemp", gname = "first.treat", tname = "year", idname = "countyreal", : 'pte' is deprecated. #> Use 'pte2' instead. #> See help("Deprecated") +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal summary(did_res) #> #> Overall ATT: #> ATT Std. Error [ 95% Conf. Int.] -#> -0.0323 0.0126 -0.057 -0.0075 * +#> -0.0323 0.0135 -0.0587 -0.0058 * #> #> #> Dynamic Effects: #> Event Time Estimate Std. Error [95% Conf. Band] -#> -3 0.0269 0.0154 -0.0131 0.0670 -#> -2 -0.0050 0.0129 -0.0385 0.0286 -#> -1 -0.0229 0.0144 -0.0603 0.0145 -#> 0 -0.0201 0.0117 -0.0506 0.0103 -#> 1 -0.0547 0.0165 -0.0976 -0.0118 * -#> 2 -0.1382 0.0396 -0.2410 -0.0354 * -#> 3 -0.1069 0.0341 -0.1954 -0.0184 * +#> -3 0.0269 0.0112 -0.0053 0.0591 +#> -2 -0.0050 0.0126 -0.0413 0.0313 +#> -1 -0.0229 0.0124 -0.0584 0.0127 +#> 0 -0.0201 0.0139 -0.0602 0.0199 +#> 1 -0.0547 0.0173 -0.1046 -0.0049 * +#> 2 -0.1382 0.0337 -0.2350 -0.0414 * +#> 3 -0.1069 0.0340 -0.2046 -0.0092 * #> --- #> Signif. codes: `*' confidence band does not cover 0 ggpte(did_res) @@ -111,7 +137,7 @@ ggpte(did_res) What’s most interesting here, is that the only “new” code that needs to be writte is in [the `did_attgt` -function](https://github.com/bcallaway11/pte/blob/master/R/attgt_functions.R). +function](https://github.com/bcallaway11/ptetools/blob/master/R/attgt_functions.R). You will see that this is a very small amount of code. ## Example 2: Policy Evaluation during a Pandemic @@ -129,7 +155,7 @@ variation in treatment timing. Therefore, it is still useful to think about group-time average treatment effects, but the DID strategy should be replaced with their particular unconfoundedness type assumption. -The `pte` package is particularly useful here. +The `ptetools` package is particularly useful here. ``` r # formula for covariates @@ -137,69 +163,151 @@ xformla <- ~ current + I(current^2) + region + totalTestResults ``` ``` r -covid_res <- pte(yname="positive", - gname="group", - tname="time.period", - idname="state_id", - data=covid_data2, - setup_pte_fun=setup_pte_basic, - subset_fun=two_by_two_subset, - attgt_fun=covid_attgt, - xformla=xformla, - max_e=21, - min_e=-10) +covid_res <- pte( + yname = "positive", + gname = "group", + tname = "time.period", + idname = "state_id", + data = covid_data2, + setup_pte_fun = setup_pte_basic, + subset_fun = two_by_two_subset, + attgt_fun = covid_attgt, + xformla = xformla, + max_e = 21, + min_e = -10 +) #> Warning in pte(yname = "positive", gname = "group", tname = "time.period", : 'pte' is deprecated. #> Use 'pte2' instead. #> See help("Deprecated") -#> Warning in compute.aggte(MP = MP, type = type, balance_e = balance_e, min_e = -#> min_e, : Simultaneous conf. band is somehow smaller than pointwise one using -#> normal approximation. Since this is unusual, we are reporting pointwise -#> confidence intervals +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal +#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than +#> critical value for pointwise confidence interval...using pointwise +#> confidence interal summary(covid_res) #> #> Overall ATT: #> ATT Std. Error [ 95% Conf. Int.] -#> 14.8882 65.6876 -113.8573 143.6336 +#> 14.8882 89.2491 -160.0369 189.8132 #> #> #> Dynamic Effects: -#> Event Time Estimate Std. Error [95% Conf. Band] -#> -10 -3.7266 3.2311 -12.3090 4.8557 -#> -9 2.6607 1.5006 -1.3252 6.6465 -#> -8 0.8290 2.2907 -5.2556 6.9136 -#> -7 5.2843 2.2970 -0.8168 11.3855 -#> -6 2.8555 1.6468 -1.5186 7.2296 -#> -5 1.3589 4.6708 -11.0476 13.7654 -#> -4 0.3294 3.4672 -8.8801 9.5388 -#> -3 -4.2227 4.1922 -15.3579 6.9125 -#> -2 -3.8447 2.9210 -11.6033 3.9138 -#> -1 -0.2234 3.4245 -9.3195 8.8727 -#> 0 -10.8156 9.3885 -35.7531 14.1218 -#> 1 -13.7998 15.7824 -55.7205 28.1209 -#> 2 -7.8432 11.4501 -38.2566 22.5703 -#> 3 -4.5541 12.2315 -37.0430 27.9347 -#> 4 -3.5368 12.3862 -36.4367 29.3631 -#> 5 8.5221 11.9115 -23.1167 40.1609 -#> 6 1.1140 16.5244 -42.7776 45.0056 -#> 7 6.6384 19.8568 -46.1044 59.3813 -#> 8 7.1288 28.8276 -69.4422 83.6998 -#> 9 10.8758 25.2019 -56.0647 77.8163 -#> 10 17.5057 32.3052 -68.3023 103.3137 -#> 11 40.8318 41.9009 -70.4639 152.1275 -#> 12 48.6134 41.2350 -60.9137 158.1404 -#> 13 52.4228 57.2359 -99.6052 204.4508 -#> 14 50.2000 71.5414 -139.8257 240.2257 -#> 15 68.2960 58.4186 -86.8735 223.4655 -#> 16 44.7305 77.2877 -160.5585 250.0195 -#> 17 61.4670 97.5688 -197.6919 320.6258 -#> 18 50.4635 96.0637 -204.6976 305.6246 -#> 19 47.3392 117.3176 -264.2759 358.9542 -#> 20 28.6326 159.2878 -394.4622 451.7275 -#> 21 4.3445 120.6413 -316.0987 324.7878 +#> Event Time Estimate Std. Error [95% Conf. Band] +#> -10 -3.7266 4.0893 -13.5376 6.0843 +#> -9 2.6607 1.4131 -0.7295 6.0508 +#> -8 0.8290 2.1182 -4.2528 5.9107 +#> -7 5.2843 2.0558 0.3523 10.2164 * +#> -6 2.8555 2.3030 -2.6698 8.3808 +#> -5 1.3589 4.0842 -8.4397 11.1575 +#> -4 0.3294 3.4489 -7.9451 8.6039 +#> -3 -4.2227 4.6681 -15.4221 6.9768 +#> -2 -3.8447 2.9548 -10.9336 3.2441 +#> -1 -0.2234 3.4588 -8.5214 8.0747 +#> 0 -10.8156 8.4755 -31.1497 9.5184 +#> 1 -13.7998 12.9474 -44.8626 17.2630 +#> 2 -7.8432 9.9894 -31.8092 16.1228 +#> 3 -4.5541 8.6319 -25.2634 16.1552 +#> 4 -3.5368 11.3025 -30.6532 23.5795 +#> 5 8.5221 12.1537 -20.6363 37.6805 +#> 6 1.1140 17.0145 -39.7064 41.9343 +#> 7 6.6384 15.9018 -31.5122 44.7891 +#> 8 7.1288 25.9489 -55.1264 69.3840 +#> 9 10.8758 33.4554 -69.3886 91.1403 +#> 10 17.5057 30.2446 -55.0556 90.0670 +#> 11 40.8318 35.3309 -43.9323 125.5959 +#> 12 48.6134 45.3943 -60.2943 157.5210 +#> 13 52.4228 59.6057 -90.5799 195.4255 +#> 14 50.2000 55.9394 -84.0068 184.4068 +#> 15 68.2960 67.1875 -92.8965 229.4885 +#> 16 44.7305 67.4749 -117.1516 206.6126 +#> 17 61.4670 82.0294 -135.3336 258.2675 +#> 18 50.4635 104.0203 -199.0964 300.0234 +#> 19 47.3392 129.1065 -262.4062 357.0845 +#> 20 28.6326 109.0253 -232.9351 290.2003 +#> 21 4.3445 129.9741 -307.4822 316.1713 #> --- #> Signif. codes: `*' confidence band does not cover 0 -ggpte(covid_res) + ylim(c(-1000,1000)) +ggpte(covid_res) + ylim(c(-1000, 1000)) ``` ![](man/figures/README-unnamed-chunk-6-1.png) @@ -219,11 +327,11 @@ Although I pretty much always end up doing this, it can be tedious, and it can be nice to get a working version of the code for a project going before working out the details on the influence function. -The `pte` package can be used with the empirical bootstrap. There are a -few limitations. First, it’s going to be substantially slower. Second, -this code just reports pointwise confidence intervals. However, this -basically is set up to fit into my typical workflow, and I see this as a -way to get preliminary results. +The `ptetools` package can be used with the empirical bootstrap. There +are a few limitations. First, it’s going to be substantially slower. +Second, this code just reports pointwise confidence intervals. However, +this basically is set up to fit into my typical workflow, and I see this +as a way to get preliminary results. Let’s demonstrate it. To do this, consider the same setup as in Example 1, but where no influence function is returned. Let’s write the code for @@ -232,7 +340,6 @@ this: ``` r # did with no influence function did_attgt_noif <- function(gt_data, xformla, ...) { - # call original function did_gt <- did_attgt(gt_data, xformla, ...) @@ -246,15 +353,17 @@ did_attgt_noif <- function(gt_data, xformla, ...) { Now, we can show the same sorts of results as above ``` r -did_res_noif <- pte(yname="lemp", - gname="first.treat", - tname="year", - idname="countyreal", - data=mpdta, - setup_pte_fun=setup_pte, - subset_fun=two_by_two_subset, - attgt_fun=did_attgt_noif, #this is only diff. - xformla=~lpop) +did_res_noif <- pte( + yname = "lemp", + gname = "first.treat", + tname = "year", + idname = "countyreal", + data = mpdta, + setup_pte_fun = setup_pte, + subset_fun = two_by_two_subset, + attgt_fun = did_attgt_noif, # this is only diff. + xformla = ~lpop +) #> Warning in pte(yname = "lemp", gname = "first.treat", tname = "year", idname = "countyreal", : 'pte' is deprecated. #> Use 'pte2' instead. #> See help("Deprecated") @@ -263,18 +372,18 @@ summary(did_res_noif) #> #> Overall ATT: #> ATT Std. Error [ 95% Conf. Int.] -#> -0.0323 0.012 -0.0558 -0.0087 * +#> -0.0323 0.0125 -0.0568 -0.0077 * #> #> #> Dynamic Effects: #> Event Time Estimate Std. Error [95% Pointwise Conf. Band] #> -3 0.0269 0.0140 -0.0005 0.0544 -#> -2 -0.0050 0.0134 -0.0312 0.0213 -#> -1 -0.0229 0.0125 -0.0473 0.0016 -#> 0 -0.0201 0.0121 -0.0439 0.0036 -#> 1 -0.0547 0.0170 -0.0881 -0.0213 * -#> 2 -0.1382 0.0332 -0.2032 -0.0732 * -#> 3 -0.1069 0.0324 -0.1704 -0.0434 * +#> -2 -0.0050 0.0131 -0.0307 0.0208 +#> -1 -0.0229 0.0155 -0.0531 0.0074 +#> 0 -0.0201 0.0123 -0.0442 0.0039 +#> 1 -0.0547 0.0170 -0.0881 -0.0214 * +#> 2 -0.1382 0.0335 -0.2039 -0.0725 * +#> 3 -0.1069 0.0344 -0.1744 -0.0394 * #> --- #> Signif. codes: `*' confidence band does not cover 0 ggpte(did_res_noif) diff --git a/TODO b/TODO index c669201..f9667c0 100644 --- a/TODO +++ b/TODO @@ -1,7 +1,7 @@ TODO: -* make sure that the knots are the same across g and t -* (I think) in the function overall_weights, work with original groups and time periods instead of the adjusted ones, but just follow what `process_att_gt` does. * I am just going to ignore the untreated group for conducting inference * it is difficult to operationalize in code - * It doesn't matter for ACRT(d) at all; for ATT(d), it doesn't matter if we interpret estimates as being nonparametric. \ No newline at end of file + * It doesn't matter for ACRT(d) at all; for ATT(d), it doesn't matter if we interpret estimates as being nonparametric. +* Report ACRT^o and ATT^o in the summary +* change text for summary of ACRT event study \ No newline at end of file diff --git a/docs/404.html b/docs/404.html index f9eb1d9..efcc0ac 100644 --- a/docs/404.html +++ b/docs/404.html @@ -5,20 +5,27 @@ -Page not found (404) • pte - +Page not found (404) • ptetools + + + + + + + + - +
@@ -46,7 +53,7 @@
  • - +
    • @@ -57,7 +64,7 @@
    - +
    @@ -85,16 +92,16 @@

    Page not found (404)

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

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    @@ -28,25 +28,25 @@
    - +
    -

    Authors

    +

    Authors and Citation

    - +
    • -

      Brantly Callaway. Author, maintainer. +

      Brantly Callaway. Author, maintainer.

    @@ -58,15 +58,15 @@

    Citation

    -

    Callaway B (2023). -pte: Panel Treatment Effects. -R package version 0.0.0.9000, https://github.com/bcallaway11/pte. +

    Callaway B (2025). +ptetools: Panel Treatment Effects Tools. +R package version 0.0.1, https://github.com/bcallaway11/pte. 

    @Manual{,
-  title = {pte: Panel Treatment Effects},
+  title = {ptetools: Panel Treatment Effects Tools},
   author = {Brantly Callaway},
-  year = {2023},
-  note = {R package version 0.0.0.9000},
+  year = {2025},
+  note = {R package version 0.0.1},
   url = {https://github.com/bcallaway11/pte},
 }
    @@ -81,15 +81,15 @@

    Citation

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

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b/docs/index.html @@ -5,21 +5,28 @@ -Panel Treatment Effects • pte - +Panel Treatment Effects Tools • ptetools + + + + + + + - - + + + - +
    @@ -47,7 +54,7 @@
  • - +
    • @@ -58,144 +65,257 @@
    - +
    -

    Panel Treatment Effects (pte) Package +

    Panel Treatment Effects Tools (ptetools) Package ptetools

    -

    The pte package compartmentalizes the steps needed to implement estimators of group-time average treatment effects (and their aggregations) in order to make it easier to apply the same sorts of arguments outside of their “birthplace” in the literature on difference-in-differences.

    +

    The ptetools package compartmentalizes the steps needed to implement estimators of group-time average treatment effects (and their aggregations) in order to make it easier to apply the same sorts of arguments outside of their “birthplace” in the literature on difference-in-differences.

    This code is lightweight, only works for balanced panels, and has minimal error checking. That said, it should be useful projects that build on top of group-time average treatment effects in order to deliver estimates of causal effects in panel data settings.

    The main function is called pte. The most important paramters that it takes in are subset_fun and attgt_fun. These are functions that the user should pass to pte.

    -

    subset_fun takes in the overall data, a group, a time period, and possibly other arguments and returns a data.frame containing the relevant subset of the data, an outcome, and whether or not a unit should be considered to be in the treated or comparison group for that group/time. There is one example of a relevant subset function provided in the package: the two_by_two_subset function. This function takes an original dataset, subsets it into pre- and post-treatment periods and denotes treated and untreated units. This particular subset is perhaps the most common/important one for thinking about treatment effects with panel data.

    -

    The other main function is attgt_fun. This function should be able to take in the correct subset of data, possibly along with other arguments to the function, and report an ATT for that subset. With minor modification, this function should be availble for most any sort of treatment effects application — for example, if you can solve the baseline 2x2 case in difference in differences, you should use that function here, and the pte package will take care of dealing with the variation in treatment timing.

    -

    If attgt_fun returns an influence function, then the pte package will also conduct inference using the multiplier bootstrap (which is fast) and produce uniform confidence bands (which adjust for multiple testing).

    +

    subset_fun takes in the overall data, a group, a time period, and possibly other arguments and returns a data.frame containing the relevant subset of the data, an outcome, and whether or not a unit should be considered to be in the treated or comparison group for that group/time. There is one example of a relevant subset function provided in the package: the two_by_two_subset function. This function takes an original dataset, subsets it into pre- and post-treatment periods and denotes treated and untreated units. This particular subset is perhaps the most common/important one for thinking about treatment effects with panel data.

    +

    The other main function is attgt_fun. This function should be able to take in the correct subset of data, possibly along with other arguments to the function, and report an ATT for that subset. With minor modification, this function should be availble for most any sort of treatment effects application — for example, if you can solve the baseline 2x2 case in difference in differences, you should use that function here, and the ptetools package will take care of dealing with the variation in treatment timing.

    +

    If attgt_fun returns an influence function, then the ptetools package will also conduct inference using the multiplier bootstrap (which is fast) and produce uniform confidence bands (which adjust for multiple testing).

    The default output of pte is an overall treatment effect on the treated (i.e., across all groups that participate in the treatment in any time period) and dynamic effects (i.e., event studies). More aggregations are possible, but these seem to be the leading cases; aggregations of group-time average treatment effects are discussed at length in Callaway and Sant’Anna (2021).

    Here are a few examples:

    Example 1: Difference in differences

    -

    The did package, which is based on Callaway and Sant’Anna (2021), includes estimates of group-time average treatment effects, ATT(g,t), based on a difference in differences identification strategy. The following example demonstrates that it is easy to compute group-time average treatment effects using difference in differences using the pte package. [Note: This is definitely not the recommended way of doing this as there is very little error handling, etc. here, but it is rather a proof of concept. You should use the did package for this case.]

    +

    The did package, which is based on Callaway and Sant’Anna (2021), includes estimates of group-time average treatment effects, ATT(g,t), based on a difference in differences identification strategy. The following example demonstrates that it is easy to compute group-time average treatment effects using difference in differences using the ptetools package. [Note: This is definitely not the recommended way of doing this as there is very little error handling, etc. here, but it is rather a proof of concept. You should use the did package for this case.]

    This example reproduces DID estimates of the effect of the minimum wage on employment using data from the did package.

     library(did)
 data(mpdta)
-did_res <- pte(yname="lemp",
-               gname="first.treat",
-               tname="year",
-               idname="countyreal",
-               data=mpdta,
-               setup_pte_fun=setup_pte,
-               subset_fun=two_by_two_subset,
-               attgt_fun=did_attgt,
-               xformla=~lpop) 
+did_res <- pte(
+  yname = "lemp",
+  gname = "first.treat",
+  tname = "year",
+  idname = "countyreal",
+  data = mpdta,
+  setup_pte_fun = setup_pte,
+  subset_fun = two_by_two_subset,
+  attgt_fun = did_attgt,
+  xformla = ~lpop
+)
+#> Warning in pte(yname = "lemp", gname = "first.treat", tname = "year", idname = "countyreal", : 'pte' is deprecated.
+#> Use 'pte2' instead.
+#> See help("Deprecated")
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
 
 summary(did_res)
 #> 
 #> Overall ATT:  
 #>      ATT    Std. Error     [ 95%  Conf. Int.]  
-#>  -0.0323        0.0111    -0.0541     -0.0104 *
+#>  -0.0323        0.0135    -0.0587     -0.0058 *
 #> 
 #> 
 #> Dynamic Effects:
 #>  Event Time Estimate Std. Error   [95%  Conf. Band]  
-#>          -3   0.0269     0.0121 -0.0036      0.0574  
-#>          -2  -0.0050     0.0131 -0.0381      0.0282  
-#>          -1  -0.0229     0.0150 -0.0607      0.0149  
-#>           0  -0.0201     0.0114 -0.0488      0.0086  
-#>           1  -0.0547     0.0167 -0.0969     -0.0126 *
-#>           2  -0.1382     0.0346 -0.2256     -0.0507 *
-#>           3  -0.1069     0.0376 -0.2019     -0.0119 *
+#>          -3   0.0269     0.0112 -0.0053      0.0591  
+#>          -2  -0.0050     0.0126 -0.0413      0.0313  
+#>          -1  -0.0229     0.0124 -0.0584      0.0127  
+#>           0  -0.0201     0.0139 -0.0602      0.0199  
+#>           1  -0.0547     0.0173 -0.1046     -0.0049 *
+#>           2  -0.1382     0.0337 -0.2350     -0.0414 *
+#>           3  -0.1069     0.0340 -0.2046     -0.0092 *
 #> ---
 #> Signif. codes: `*' confidence band does not cover 0
 ggpte(did_res)

    -

    What’s most interesting here, is that the only “new” code that needs to be writte is in the did_attgt function. You will see that this is a very small amount of code.

    +

    What’s most interesting here, is that the only “new” code that needs to be writte is in the did_attgt function. You will see that this is a very small amount of code.

    Example 2: Policy Evaluation during a Pandemic

    As a next example, consider trying to estimate effects of Covid-19 related policies during a pandemic. The estimates below are for the effects of state-leve shelter-in-place orders during the early part of the pandemic.

    Callaway and Li (2021) argue that a particular unconfoundedness-type strategy is more appropriate in this context than DID-type strategies due to the spread of Covid-19 cases being highly nonlinear. However, they still deal with the challenge of variation in treatment timing. Therefore, it is still useful to think about group-time average treatment effects, but the DID strategy should be replaced with their particular unconfoundedness type assumption.

    -

    The pte package is particularly useful here.

    +

    The ptetools package is particularly useful here.

     # formula for covariates
 xformla <- ~ current + I(current^2) + region + totalTestResults
    -covid_res <- pte(yname="positive",
-                 gname="group",
-                 tname="time.period",
-                 idname="state_id",
-                 data=covid_data2,
-                 setup_pte_fun=setup_pte_basic,
-                 subset_fun=two_by_two_subset,
-                 attgt_fun=covid_attgt,
-                 xformla=xformla,
-                 max_e=21,
-                 min_e=-10) 
-#> Warning in compute.aggte(MP = MP, type = type, balance_e = balance_e, min_e =
-#> min_e, : Simultaneous conf. band is somehow smaller than pointwise one using
-#> normal approximation. Since this is unusual, we are reporting pointwise
-#> confidence intervals
+covid_res <- pte(
+  yname = "positive",
+  gname = "group",
+  tname = "time.period",
+  idname = "state_id",
+  data = covid_data2,
+  setup_pte_fun = setup_pte_basic,
+  subset_fun = two_by_two_subset,
+  attgt_fun = covid_attgt,
+  xformla = xformla,
+  max_e = 21,
+  min_e = -10
+)
+#> Warning in pte(yname = "positive", gname = "group", tname = "time.period", : 'pte' is deprecated.
+#> Use 'pte2' instead.
+#> See help("Deprecated")
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
+#> Warning in mboot2(thisinffunc, biters = biters, alp = alp): critical value for uniform confidence band is somehow smaller than
+#>             critical value for pointwise confidence interval...using pointwise
+#>             confidence interal
 
 summary(covid_res)
 #> 
 #> Overall ATT:  
 #>      ATT    Std. Error     [ 95%  Conf. Int.] 
-#>  14.8882       83.8907  -149.5347     179.311 
+#>  14.8882       89.2491  -160.0369    189.8132 
 #> 
 #> 
 #> Dynamic Effects:
-#>  Event Time Estimate Std. Error     [95%  Conf. Band] 
-#>         -10  -3.7266     3.8545  -14.3422      6.8889 
-#>          -9   2.6607     1.6804   -1.9672      7.2886 
-#>          -8   0.8290     2.1834   -5.1843      6.8422 
-#>          -7   5.2843     2.5252   -1.6703     12.2390 
-#>          -6   2.8555     2.0553   -2.8050      8.5160 
-#>          -5   1.3589     4.8250  -11.9293     14.6471 
-#>          -4   0.3294     4.4997  -12.0631     12.7219 
-#>          -3  -4.2227     5.5764  -19.5802     11.1349 
-#>          -2  -3.8447     2.6764  -11.2157      3.5263 
-#>          -1  -0.2234     4.1228  -11.5778     11.1310 
-#>           0 -10.8156     7.4650  -31.3747      9.7434 
-#>           1 -13.7998    14.9400  -54.9455     27.3458 
-#>           2  -7.8432    12.4921  -42.2471     26.5608 
-#>           3  -4.5541     9.7413  -31.3821     22.2738 
-#>           4  -3.5368    12.2911  -37.3872     30.3136 
-#>           5   8.5221    13.1051  -27.5701     44.6143 
-#>           6   1.1140    15.0092  -40.2220     42.4500 
-#>           7   6.6384    23.7749  -58.8389     72.1158 
-#>           8   7.1288    27.8035  -69.4435     83.7011 
-#>           9  10.8758    26.7418  -62.7725     84.5241 
-#>          10  17.5057    30.7139  -67.0821    102.0935 
-#>          11  40.8318    41.3370  -73.0124    154.6760 
-#>          12  48.6134    56.0856 -105.8492    203.0759 
-#>          13  52.4228    55.8698 -101.4455    206.2911 
-#>          14  50.2000    48.6461  -83.7737    184.1738 
-#>          15  68.2960    58.0243  -91.5059    228.0980 
-#>          16  44.7305    63.8813 -131.2018    220.6629 
-#>          17  61.4670    82.5996 -166.0166    288.9506 
-#>          18  50.4635   107.8083 -246.4461    347.3731 
-#>          19  47.3392   116.1415 -272.5204    367.1987 
-#>          20  28.6326   152.9542 -392.6110    449.8763 
-#>          21   4.3445   129.9832 -353.6357    362.3248 
+#>  Event Time Estimate Std. Error     [95%  Conf. Band]  
+#>         -10  -3.7266     4.0893  -13.5376      6.0843  
+#>          -9   2.6607     1.4131   -0.7295      6.0508  
+#>          -8   0.8290     2.1182   -4.2528      5.9107  
+#>          -7   5.2843     2.0558    0.3523     10.2164 *
+#>          -6   2.8555     2.3030   -2.6698      8.3808  
+#>          -5   1.3589     4.0842   -8.4397     11.1575  
+#>          -4   0.3294     3.4489   -7.9451      8.6039  
+#>          -3  -4.2227     4.6681  -15.4221      6.9768  
+#>          -2  -3.8447     2.9548  -10.9336      3.2441  
+#>          -1  -0.2234     3.4588   -8.5214      8.0747  
+#>           0 -10.8156     8.4755  -31.1497      9.5184  
+#>           1 -13.7998    12.9474  -44.8626     17.2630  
+#>           2  -7.8432     9.9894  -31.8092     16.1228  
+#>           3  -4.5541     8.6319  -25.2634     16.1552  
+#>           4  -3.5368    11.3025  -30.6532     23.5795  
+#>           5   8.5221    12.1537  -20.6363     37.6805  
+#>           6   1.1140    17.0145  -39.7064     41.9343  
+#>           7   6.6384    15.9018  -31.5122     44.7891  
+#>           8   7.1288    25.9489  -55.1264     69.3840  
+#>           9  10.8758    33.4554  -69.3886     91.1403  
+#>          10  17.5057    30.2446  -55.0556     90.0670  
+#>          11  40.8318    35.3309  -43.9323    125.5959  
+#>          12  48.6134    45.3943  -60.2943    157.5210  
+#>          13  52.4228    59.6057  -90.5799    195.4255  
+#>          14  50.2000    55.9394  -84.0068    184.4068  
+#>          15  68.2960    67.1875  -92.8965    229.4885  
+#>          16  44.7305    67.4749 -117.1516    206.6126  
+#>          17  61.4670    82.0294 -135.3336    258.2675  
+#>          18  50.4635   104.0203 -199.0964    300.0234  
+#>          19  47.3392   129.1065 -262.4062    357.0845  
+#>          20  28.6326   109.0253 -232.9351    290.2003  
+#>          21   4.3445   129.9741 -307.4822    316.1713  
 #> ---
 #> Signif. codes: `*' confidence band does not cover 0
-ggpte(covid_res) + ylim(c(-1000,1000))
    +ggpte(covid_res) + ylim(c(-1000, 1000))

    -

    What’s most interesting is just how little code needs to be written here. The only new code required is the ppe::covid_attgt function which is available here, and, as you can see, this is very simple.

    +

    What’s most interesting is just how little code needs to be written here. The only new code required is the ppe::covid_attgt function which is available here, and, as you can see, this is very simple.

    Example 3: Empirical Bootstrap

    The code above used the multiplier bootstrap. The great thing about the multiplier bootstrap is that it’s fast. But in order to use it, you have to work out the influence function for the estimator of ATT(g,t). Although I pretty much always end up doing this, it can be tedious, and it can be nice to get a working version of the code for a project going before working out the details on the influence function.

    -

    The pte package can be used with the empirical bootstrap. There are a few limitations. First, it’s going to be substantially slower. Second, this code just reports pointwise confidence intervals. However, this basically is set up to fit into my typical workflow, and I see this as a way to get preliminary results.

    +

    The ptetools package can be used with the empirical bootstrap. There are a few limitations. First, it’s going to be substantially slower. Second, this code just reports pointwise confidence intervals. However, this basically is set up to fit into my typical workflow, and I see this as a way to get preliminary results.

    Let’s demonstrate it. To do this, consider the same setup as in Example 1, but where no influence function is returned. Let’s write the code for this:

     # did with no influence function
 did_attgt_noif <- function(gt_data, xformla, ...) {
-
   # call original function
   did_gt <- did_attgt(gt_data, xformla, ...)
 
@@ -206,32 +326,37 @@ 
    Example 3: Empirical Bootstrap}

    Now, we can show the same sorts of results as above

    -did_res_noif <- pte(yname="lemp",
-                    gname="first.treat",
-                    tname="year",
-                    idname="countyreal",
-                    data=mpdta,
-                    setup_pte_fun=setup_pte,
-                    subset_fun=two_by_two_subset,
-                    attgt_fun=did_attgt_noif, #this is only diff.
-                    xformla=~lpop) 
+did_res_noif <- pte(
+  yname = "lemp",
+  gname = "first.treat",
+  tname = "year",
+  idname = "countyreal",
+  data = mpdta,
+  setup_pte_fun = setup_pte,
+  subset_fun = two_by_two_subset,
+  attgt_fun = did_attgt_noif, # this is only diff.
+  xformla = ~lpop
+)
+#> Warning in pte(yname = "lemp", gname = "first.treat", tname = "year", idname = "countyreal", : 'pte' is deprecated.
+#> Use 'pte2' instead.
+#> See help("Deprecated")
 
 summary(did_res_noif)
 #> 
 #> Overall ATT:  
 #>      ATT    Std. Error     [ 95%  Conf. Int.]  
-#>  -0.0323        0.0137     -0.059     -0.0055 *
+#>  -0.0323        0.0125    -0.0568     -0.0077 *
 #> 
 #> 
 #> Dynamic Effects:
 #>  Event Time Estimate Std. Error [95% Pointwise  Conf. Band]  
-#>          -3   0.0269     0.0133          0.0009      0.0529 *
-#>          -2  -0.0050     0.0131         -0.0306      0.0207  
-#>          -1  -0.0229     0.0166         -0.0555      0.0097  
-#>           0  -0.0201     0.0130         -0.0455      0.0052  
-#>           1  -0.0547     0.0176         -0.0893     -0.0202 *
-#>           2  -0.1382     0.0378         -0.2122     -0.0642 *
-#>           3  -0.1069     0.0338         -0.1732     -0.0406 *
+#>          -3   0.0269     0.0140         -0.0005      0.0544  
+#>          -2  -0.0050     0.0131         -0.0307      0.0208  
+#>          -1  -0.0229     0.0155         -0.0531      0.0074  
+#>           0  -0.0201     0.0123         -0.0442      0.0039  
+#>           1  -0.0547     0.0170         -0.0881     -0.0214 *
+#>           2  -0.1382     0.0335         -0.2039     -0.0725 *
+#>           3  -0.1069     0.0344         -0.1744     -0.0394 *
 #> ---
 #> Signif. codes: `*' confidence band does not cover 0
 ggpte(did_res_noif)
    @@ -260,7 +385,7 @@

    License

    Citation

    @@ -284,16 +409,16 @@

    Developers

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

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    +
    + + + +
    +
    +
    +

    aggte_obj

    + Source: R/pte_aggte.R + +
    + +
    +

    Objects of this class hold results on aggregated +group-time average treatment effects. This is derived from the AGGTEobj +class in the did package.

    +

    An object for holding aggregated treatment effect parameters.

    +
    + +
    + 
    aggte_obj(
+  overall.att = NULL,
+  overall.se = NULL,
+  type = "simple",
+  egt = NULL,
+  att.egt = NULL,
+  se.egt = NULL,
+  crit.val.egt = NULL,
+  inf.function = NULL,
+  min_e = NULL,
+  max_e = NULL,
+  balance_e = NULL,
+  call = NULL,
+  DIDparams = NULL
+)
    +
    + +
    +

    Arguments

    + + +
    overall.att
    +

    The estimated overall ATT

    + + +
    overall.se
    +

    Standard error for overall ATT

    + + +
    egt
    +

    Holds the length of exposure (for dynamic effects), the +group (for selective treatment timing), or the time period (for calendar +time effects)

    + + +
    att.egt
    +

    The ATT specific to egt

    + + +
    se.egt
    +

    The standard error specific to egt

    + + +
    crit.val.egt
    +

    A critical value for computing uniform confidence +bands for dynamic effects, selective treatment timing, or time period +effects.

    + + +
    inf.function
    +

    The influence function of the chosen aggregated parameters

    + + +
    DIDparams
    +

    A DIDparams object

    + +
    +
    +

    Value

    +

    an aggte_obj

    +
    + +
    + +
    + + +
    +

    Developed by Brantly Callaway.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/attgt_if.html b/docs/reference/attgt_if.html index 50c004f..1ee3317 100644 --- a/docs/reference/attgt_if.html +++ b/docs/reference/attgt_if.html @@ -1,10 +1,10 @@ -attgt_if — attgt_if • pteattgt_if — attgt_if • ptetools - +
    @@ -29,14 +29,14 @@
    - +
    @@ -57,15 +57,17 @@

    attgt_if

    Arguments

    -
    attgt
    + + +
    attgt

    group-time average treatment effect

    -
    inf_func
    +
    inf_func

    influence function

    -
    extra_gt_returns
    +
    extra_gt_returns

    A place to return anything extra from particular group-time average treatment effect calculations. For DID, this might be something like propensity score estimates, regressions of untreated @@ -76,9 +78,7 @@

    Arguments

    Value

    - - -

    attgt_if object

    +

    attgt_if object

    @@ -93,15 +93,15 @@

    Value

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/attgt_noif.html b/docs/reference/attgt_noif.html index 4f7aecf..68d9347 100644 --- a/docs/reference/attgt_noif.html +++ b/docs/reference/attgt_noif.html @@ -1,10 +1,10 @@ -attgt_noif — attgt_noif • pteattgt_noif — attgt_noif • ptetools - +
    @@ -29,14 +29,14 @@
    - +
    @@ -57,11 +57,13 @@

    attgt_noif

    Arguments

    -
    attgt
    + + +
    attgt

    group-time average treatment effect

    -
    extra_gt_returns
    +
    extra_gt_returns

    A place to return anything extra from particular group-time average treatment effect calculations. For DID, this might be something like propensity score estimates, regressions of untreated @@ -72,9 +74,7 @@

    Arguments

    Value

    - - -

    attgt_noif object

    +

    attgt_noif object

    @@ -89,15 +89,15 @@

    Value

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/attgt_pte_aggregations.html b/docs/reference/attgt_pte_aggregations.html index 909d448..8bd0f13 100644 --- a/docs/reference/attgt_pte_aggregations.html +++ b/docs/reference/attgt_pte_aggregations.html @@ -1,12 +1,12 @@ -attgt_pte_aggregations — attgt_pte_aggregations • pteattgt_pte_aggregations — attgt_pte_aggregations • ptetools - +
    @@ -31,14 +31,14 @@
    - +
    @@ -61,19 +61,19 @@

    attgt_pte_aggregations

    Arguments

    -
    attgt.list
    + + +
    attgt.list

    list of attgt results from compute.pte

    -
    ptep
    +
    ptep

    pte_params object

    Value

    - - -

    pte_emp_boot object

    +

    pte_emp_boot object

    @@ -88,15 +88,15 @@

    Value

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/compute.pte.html b/docs/reference/compute.pte.html index 2263284..6c98b08 100644 --- a/docs/reference/compute.pte.html +++ b/docs/reference/compute.pte.html @@ -1,9 +1,9 @@ -compute.pte — compute.pte • ptecompute.pte — compute.pte • ptetools - +
    @@ -28,14 +28,14 @@
    - +
    @@ -55,11 +55,13 @@

    compute.pte

    Arguments

    -
    ptep
    + + +
    ptep

    pte_params object

    -
    subset_fun
    +
    subset_fun

    This is a function that should take in data, g (for group), tp (for time period), and ... and be able to return the appropriate data.frame that can be used @@ -69,7 +71,7 @@

    Arguments

    belongs to, etc.

    -
    attgt_fun
    +
    attgt_fun

    This is a function that should work in the case where there is a single group and the "right" number of time periods to recover an estimate of the ATT. For example, in the contest of @@ -97,7 +99,7 @@

    Arguments

    substantially) computationally slower.

    -
    ...
    +
    ...

    extra arguments that can be passed to create the correct subsets of the data (depending on subset_fun), to estimate group time average treatment effects (depending on attgt_fun), or to @@ -107,9 +109,7 @@

    Arguments

    Value

    - - -

    list of attgt results and, sometimes, and influence function

    +

    list of attgt results and, sometimes, and influence function

    @@ -124,15 +124,15 @@

    Value

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/compute.pte2.html b/docs/reference/compute.pte2.html index 156bdb5..59f2648 100644 --- a/docs/reference/compute.pte2.html +++ b/docs/reference/compute.pte2.html @@ -1,12 +1,12 @@ -compute.pte2 — compute.pte2 • ptecompute.pte2 — compute.pte2 • ptetools - +
    @@ -31,14 +31,14 @@
    - +
    @@ -56,16 +56,18 @@

    compute.pte2

    - 
    compute.pte2(ptep, subset_fun, attgt_fun, global_model = FALSE, ...)
    + 
    compute.pte2(ptep, subset_fun, attgt_fun, ...)

    Arguments

    -
    ptep
    + + +
    ptep

    pte_params object

    -
    subset_fun
    +
    subset_fun

    This is a function that should take in data, g (for group), tp (for time period), and ... and be able to return the appropriate data.frame that can be used @@ -75,7 +77,7 @@

    Arguments

    belongs to, etc.

    -
    attgt_fun
    +
    attgt_fun

    This is a function that should work in the case where there is a single group and the "right" number of time periods to recover an estimate of the ATT. For example, in the contest of @@ -103,7 +105,7 @@

    Arguments

    substantially) computationally slower.

    -
    ...
    +
    ...

    extra arguments that can be passed to create the correct subsets of the data (depending on subset_fun), to estimate group time average treatment effects (depending on attgt_fun), or to @@ -113,9 +115,7 @@

    Arguments

    Value

    - - -

    list of attgt results and, sometimes, an influence function

    +

    list of attgt results and, sometimes, an influence function

    @@ -130,15 +130,15 @@

    Value

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/crit_val_checks.html b/docs/reference/crit_val_checks.html new file mode 100644 index 0000000..da8c46e --- /dev/null +++ b/docs/reference/crit_val_checks.html @@ -0,0 +1,98 @@ + +crit_val_checks — crit_val_checks • ptetools + + +
    +
    + + + +
    +
    +
    +

    crit_val_checks

    + Source: R/pte_aggte.R + +
    + +
    +

    A function to perform sanity checks and possibly adjust a +a critical value to form a uniform confidence band

    +
    + +
    + 
    crit_val_checks(crit_val, alp = 0.05)
    +
    + +
    +

    Arguments

    + + +
    crit_val
    +

    the critical value

    + + +
    alp
    +

    the significance level

    + +
    +
    +

    Value

    +

    a (possibly adjusted) critical value

    +
    + +
    + +
    + + +
    +

    Developed by Brantly Callaway.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/did_attgt.html b/docs/reference/did_attgt.html index e347109..b2f6f70 100644 --- a/docs/reference/did_attgt.html +++ b/docs/reference/did_attgt.html @@ -1,5 +1,5 @@ -did_attgt — did_attgt • pte - +
    @@ -38,14 +38,14 @@
    - +
    @@ -65,7 +65,7 @@

    did_attgt

    D (treated group identifier), period (time period), name (equal to "pre" for pre-treatment periods and equal to "post" for post treatment periods), Y (outcome).

    -

    In our case, we call pte::two_by_two_subset which sets up the +

    In our case, we call pte::two_by_two_subset which sets up the data to have this format before the call to did_attgt.

    @@ -75,25 +75,25 @@

    did_attgt

    Arguments

    -
    gt_data
    + + +
    gt_data

    data that is "local" to a particular group-time average treatment effect

    -
    xformla
    +
    xformla

    one-sided formula for covariates used in the propensity score and outcome regression models

    -
    ...
    +
    ...

    extra function arguments; not used here

    Value

    - - -

    attgt_if

    +

    attgt_if

    @@ -108,15 +108,15 @@

    Value

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/dose_obj.html b/docs/reference/dose_obj.html new file mode 100644 index 0000000..e3106f0 --- /dev/null +++ b/docs/reference/dose_obj.html @@ -0,0 +1,151 @@ + +dose_obj — dose_obj • ptetools + + +
    +
    + + + +
    +
    +
    +

    dose_obj

    + Source: R/process_dose_gt.R + +
    + +
    +

    Holds results from computing dose-specific treatment effects +with a continuous treatment

    +
    + +
    + 
    dose_obj(
+  dose,
+  att.d = NULL,
+  att.d_se = NULL,
+  att.d_crit.val = NULL,
+  att.d_inffunc = NULL,
+  acrt.d = NULL,
+  acrt.d_se = NULL,
+  acrt.d_crit.val = NULL,
+  acrt.d_inffunc = NULL,
+  pte_params = NULL,
+  call = NULL
+)
    +
    + +
    +

    Arguments

    + + +
    dose
    +

    vector containing the values of the dose used in estimation

    + + +
    att.d
    +

    estimates of ATT(d) for each value of dose

    + + +
    att.d_se
    +

    standard error of ATT(d) for each value of dose

    + + +
    att.d_inffunc
    +

    matrix containing the influence function from estimating +ATT(d)

    + + +
    acrt.d
    +

    estimates of ACRT(d) for each value of dose

    + + +
    acrt.d_se
    +

    standard error of ACRT(d) for each value of dose

    + + +
    acrt.d_inffunc
    +

    matrix containing the influence function from estimating +ACRT(d)

    + + +
    pte_params
    +

    a pte_params object containing other parameters passed to the function

    + + +
    call
    +

    the original call to the function for computing causal effect parameters +with a continuous treatment

    + + +
    att.d_crt.val
    +

    critical value to produce pointwise or uniform confidence +interval for ATT(d)

    + + +
    acrt.d_crt.val
    +

    critical value to produce pointwise or uniform confidence +interval for ACRT(d)

    + +
    +
    +

    Value

    +

    dose_obj

    +
    + +
    + +
    + + +
    +

    Developed by Brantly Callaway.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
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zGxyH?W6AcrF_4zehhU$n+d-_?Cp5EP4y1YN)z2yl@pi(9T{#7Bw#Ui2t83LY)6(AP z1?j`5y4kZ3pX=Q2`dd+WgWV+oiEk+yicbl7 z$!zDhp1A#4j|iRTv%?dYB0?cpCGVpgYm*()HiQ}7uD>x9+=nL2@GV%1@FDX)!HuFtz^2PGO4GyQqUoU@W4=18}e9|B!1 zB{%i9(-!$uQpdP_<`Y*P@*50y{axu#@c^b6*ugH&QBb@GmAh^?(1JBjTBYWZq*6~8 zqdI!bkjNoMb*-Q@hY7(ydtU3H|PCRSzs_o)z0A8V=*72YxFRqbCY?2=1fwPiJc{~e>mV4-&NBmvEfpS zcW2)>d!mNluO$dFeKdaB$IU9Y# zd_9L6Wiedw0~j*)GM#)L+8-1QaEmyK50vUw(>)>{PE^e>%9)FpXMd^N!&)+K=>Uk@ z4SYFMI|DyW^Q8%M9Lf}P3$0~oiJ7M{Ej?T-wPp|Z{;&V^t$N!*h#L5(0H{i-WTH__ zE8!$;qE=;&cM9&ze>zuKEawxz2v&~J+zjdY3yd%?1RL4}yE+BC!CV5}zz>zOqOuB9 zQ4KtnN*XXFC76neoT4I3QIYBC;nV-sz{k(k^WMY%yTOAIeR +Take influence function and return standard errors — getSE • ptetools + + +

    +
    + + + +
    +
    +
    +

    Take influence function and return standard errors

    + Source: R/pte_aggte.R + +
    + +
    +

    Function to take an nx1 influence function and return +a standard error

    +
    + +
    + 
    getSE(thisinffunc, bstrap = TRUE, biters = 100, alp = 0.05)
    +
    + +
    +

    Arguments

    + + +
    thisinffunc
    +

    An influence function

    + +
    +
    +

    Value

    +

    scalar standard error

    +
    + +
    + +
    + + +
    +

    Developed by Brantly Callaway.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/get_agg_inf_func.html b/docs/reference/get_agg_inf_func.html new file mode 100644 index 0000000..3daab69 --- /dev/null +++ b/docs/reference/get_agg_inf_func.html @@ -0,0 +1,118 @@ + +Get an influence function for particular aggregate parameters — get_agg_inf_func • ptetools + + +
    +
    + + + +
    +
    +
    +

    Get an influence function for particular aggregate parameters

    + Source: R/pte_aggte.R + +
    + +
    +

    Get an influence function for particular aggregate parameters

    +

    This is a generic internal function for combining influence +functions across ATT(g,t)'s to return an influence function for +various aggregated treatment effect parameters.

    +
    + +
    + 
    get_agg_inf_func(att, inffunc1, whichones, weights.agg, wif = NULL)
    +
    + +
    +

    Arguments

    + + +
    att
    +

    vector of group-time average treatment effects

    + + +
    inffunc1
    +

    influence function for all group-time average treatment effects +(matrix)

    + + +
    whichones
    +

    which elements of att will be used to compute the aggregated +treatment effect parameter

    + + +
    weights.agg
    +

    the weights to apply to each element of att(whichones); +should have the same dimension as att(whichones)

    + + +
    wif
    +

    extra influence function term coming from estimating the weights; +should be n x k matrix where k is dimension of whichones

    + +
    +
    +

    Value

    +

    nx1 influence function

    +
    + +
    + +
    + + +
    +

    Developed by Brantly Callaway.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/ggpte.html b/docs/reference/ggpte.html index 6878688..058e616 100644 --- a/docs/reference/ggpte.html +++ b/docs/reference/ggpte.html @@ -1,9 +1,9 @@ -ggpte — ggpte • pteggpte — ggpte • ptetools - +
    @@ -28,14 +28,14 @@
    - +
    @@ -55,7 +55,9 @@

    ggpte

    Arguments

    -
    pte_results
    + + +
    pte_results

    A pte_results object

    @@ -72,15 +74,15 @@

    Arguments

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/ggpte_cont.html b/docs/reference/ggpte_cont.html new file mode 100644 index 0000000..2e20dd7 --- /dev/null +++ b/docs/reference/ggpte_cont.html @@ -0,0 +1,93 @@ + +ggpte_cont — ggpte_cont • ptetools + + +
    +
    + + + +
    +
    +
    +

    ggpte_cont

    + Source: R/ggpte.R + +
    + +
    +

    a function for plotting results in applications with a continuous treatment

    +
    + +
    + 
    ggpte_cont(dose_obj, type = "att")
    +
    + +
    +

    Arguments

    + + +
    dose_obj
    +

    a dose_obj that holds results with a continuous treatment

    + + +
    type
    +

    whether to plot ATT(d) or ACRT(d), defaults to att for +plotting ATT(d). For ACRT(d), use "acrt"

    + +
    + +
    + +
    + + +
    +

    Developed by Brantly Callaway.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/group_time_att.html b/docs/reference/group_time_att.html index fcd6146..b48becd 100644 --- a/docs/reference/group_time_att.html +++ b/docs/reference/group_time_att.html @@ -1,9 +1,9 @@ -group_time_att — group_time_att • ptegroup_time_att — group_time_att • ptetools - +
    @@ -28,14 +28,14 @@
    - +
    @@ -70,65 +70,71 @@

    group_time_att

    Arguments

    -
    group
    + + +
    group

    numeric vector of groups for ATT(g,t)

    -
    time.period
    +
    time.period

    numeric vector of time periods for ATT(g,t)

    -
    att
    +
    att

    numeric vector containing the value of ATT(g,t) for corresponding group and time period

    -
    V_analytical
    +
    V_analytical

    analytical asymptotic variance matrix for ATT(g,t)'s

    -
    se
    +
    se

    numeric vector of standard errors

    -
    crit_val
    +
    crit_val

    critical value (usually a critical value for conducting uniform inference)

    -
    inf_func
    +
    inf_func

    matrix of influence function

    -
    n
    +
    n

    number of unique individuals

    -
    W
    +
    W

    Wald statistic for ATT(g,t) version of pre-test of parallel trends assumption

    -
    Wpval
    +
    Wpval

    p-value for Wald pre-test of ATT(g,t) version of parallel trends assumption

    -
    alp
    +
    cband
    +

    logical indicating whether or not to report a confidence band

    + + +
    alp

    significance level

    -
    ptep
    +
    ptep

    pte_params object

    + +
    extra_gt_returns
    +

    list containing extra returns at the group-time level

    +

    Value

    - - -

    object of class group_time_att

    - - +

    object of class group_time_att

    @@ -143,15 +149,15 @@

    Value

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/gt_data_frame.html b/docs/reference/gt_data_frame.html index 5203bf2..5af931a 100644 --- a/docs/reference/gt_data_frame.html +++ b/docs/reference/gt_data_frame.html @@ -1,11 +1,11 @@ -gt_data_frame — gt_data_frame • ptegt_data_frame — gt_data_frame • ptetools - +
    @@ -30,14 +30,14 @@
    - +
    @@ -59,16 +59,16 @@

    gt_data_frame

    Arguments

    -
    data
    + + +
    data

    data that will be checked to see if has right format for computing group-time average treatment effects

    Value

    - - -

    gt_data_frame object

    +

    gt_data_frame object

    @@ -83,15 +83,15 @@

    Value

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/index.html b/docs/reference/index.html index 79eb3b7..8c3a531 100644 --- a/docs/reference/index.html +++ b/docs/reference/index.html @@ -1,9 +1,9 @@ -Function reference • ptePackage index • ptetools - +
    @@ -28,14 +28,14 @@
    - +
    @@ -48,6 +48,10 @@

    All functions

    +

    aggte_obj()

    + +

    aggte_obj

    +

    attgt_if()

    attgt_if

    @@ -67,14 +71,26 @@

    All functions compute.pte2()

    compute.pte2

    + +

    crit_val_checks()

    + +

    crit_val_checks

    did_attgt()

    did_attgt

    + +

    dose_obj()

    + +

    dose_obj

    ggpte()

    ggpte

    + +

    ggpte_cont()

    + +

    ggpte_cont

    group_time_att()

    @@ -83,14 +99,22 @@

    All functions gt_data_frame()

    gt_data_frame

    + +

    keep_all_pretreatment_subset()

    + +

    keep_all_pretreatment_subset

    + +

    keep_all_untreated_subset()

    + +

    keep_all_untreated_subset

    mboot2()

    mboot2

    -

    orig2t()

    +

    overall_weights()

    -

    orig2t

    +

    overall_weights

    panel_empirical_bootstrap()

    @@ -103,6 +127,10 @@

    All functions print(<pte_results>)

    print.pte_results

    + +

    print(<summary.dose_obj>)

    + +

    print.summary.dose_obj

    print(<summary.pte_results>)

    @@ -122,15 +150,7 @@

    All functions

    pte_aggte()

    -

    pte_aggte - -This is a slight edit of the aggte function from the did package. -Currently, it only provides aggregations for "overall" treatment effects -and event studies. It also will provide the weights directly which is -currently used for constructing aggregations based on distributions. -The other difference is that, pte_aggte provides inference results -where the only randomness is coming from the outcomes (not from the group -assignment nor from the covariates).

    +

    pte_aggte

    pte_attgt()

    @@ -139,6 +159,10 @@

    All functions pte_default()

    pte_default

    + +

    pte_dose_results()

    + +

    pte_dose_results

    pte_emp_boot()

    @@ -167,6 +191,14 @@

    All functions setup_pte_basic()

    Example setup panel treatment effects parameters

    + +

    summary(<aggte_obj>)

    + +

    Summary Aggregate Treatment Effect Parameter Objects

    + +

    summary(<dose_obj>)

    + +

    summary.dose_obj

    summary(<group_time_att>)

    @@ -179,10 +211,6 @@

    All functions summary(<pte_results>)

    summary.pte_results

    - -

    t2orig()

    - -

    t2orig

    two_by_two_subset()

    @@ -200,15 +228,15 @@

    All functions
    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/keep_all_pretreatment_subset.html b/docs/reference/keep_all_pretreatment_subset.html new file mode 100644 index 0000000..3aeca02 --- /dev/null +++ b/docs/reference/keep_all_pretreatment_subset.html @@ -0,0 +1,116 @@ + +keep_all_pretreatment_subset — keep_all_pretreatment_subset • ptetools + + +
    +
    + + + +
    +
    +
    +

    keep_all_pretreatment_subset

    + Source: R/subset_functions.R + +
    + +
    +

    A function that takes an original data set and keeps all +data for all groups that are not-yet-treated by period tp as well +as for group g.

    +

    In particular, this keeps more data than functions like two_by_two +subset that use a fixed base period.

    +

    A main use case for this function is the interactive fixed effects approach +proposed in Callaway and Tsyawo (2023).

    +
    + +
    + 
    keep_all_pretreatment_subset(data, g, tp, ...)
    +
    + +
    +

    Arguments

    + + +
    data
    +

    the full dataset

    + + +
    g
    +

    the current group

    + + +
    tp
    +

    the current time period

    + + +
    ...
    +

    additional arguments

    + +
    +
    +

    Value

    +

    all data but in correct format for computing ATT(g,t)

    +
    + +
    + +
    + + +
    +

    Developed by Brantly Callaway.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/keep_all_untreated_subset.html b/docs/reference/keep_all_untreated_subset.html new file mode 100644 index 0000000..b1f69d0 --- /dev/null +++ b/docs/reference/keep_all_untreated_subset.html @@ -0,0 +1,120 @@ + +keep_all_untreated_subset — keep_all_untreated_subset • ptetools + + +
    +
    + + + +
    +
    +
    +

    keep_all_untreated_subset

    + Source: R/subset_functions.R + +
    + +
    +

    A function that takes an original data set and keeps all +pre-treatment data for all groups. For group g, it also includes data +for the current period.

    +

    Also, note that if tp is still a pre-treatment period for group g, +then periods after tp will also be dropped for group g. This is a +design choice and is useful especially for estimating placebo +group-time average treatment effects in pre-treatment periods.

    +

    A main use case for this function is to compute ATT(g,t)'s using a global +estimation strategy such as imputation in Gardner (2022).

    +
    + +
    + 
    keep_all_untreated_subset(data, g, tp, ...)
    +
    + +
    +

    Arguments

    + + +
    data
    +

    the full dataset

    + + +
    g
    +

    the current group

    + + +
    tp
    +

    the current time period

    + + +
    ...
    +

    extra arguments to get the subset correct

    + +
    +
    +

    Value

    +

    all data but in correct format for computing ATT(g,t)

    +
    + +
    + +
    + + +
    +

    Developed by Brantly Callaway.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/mboot2.html b/docs/reference/mboot2.html index 2f23024..6a2e43a 100644 --- a/docs/reference/mboot2.html +++ b/docs/reference/mboot2.html @@ -1,10 +1,10 @@ -mboot2 — mboot2 • ptemboot2 — mboot2 • ptetools - +
    @@ -29,14 +29,14 @@
    - +
    @@ -57,15 +57,17 @@

    mboot2

    Arguments

    -
    inffunc
    + + +
    inffunc

    influence function matrix

    -
    biters
    +
    biters

    number of bootstrap iterations; default is 100

    -
    alp
    +
    alp

    significance level; default is 0.05

    @@ -82,15 +84,15 @@

    Arguments

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/overall_weights.html b/docs/reference/overall_weights.html new file mode 100644 index 0000000..8ff2dbd --- /dev/null +++ b/docs/reference/overall_weights.html @@ -0,0 +1,96 @@ + +overall_weights — overall_weights • ptetools + + +
    +
    + + + +
    +
    +
    +

    overall_weights

    + Source: R/pte_aggte.R + +
    + +
    +

    A function that returns weights on gt's to deliver overall +(averaged across groups and time periods) treatment effect parameters

    +
    + +
    + 
    overall_weights(attgt, balance_e = NULL, min_e = -Inf, max_e = Inf, ...)
    +
    + +
    +

    Arguments

    + + +
    attgt
    +

    A group_time_att object to be aggregated

    + +
    +
    +

    Value

    +

    a data.frame with columns containing the group, the time period +and the amount of weight that it should get for an overall treatment +effect parameter

    +
    + +
    + +
    + + +
    +

    Developed by Brantly Callaway.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/panel_empirical_bootstrap.html b/docs/reference/panel_empirical_bootstrap.html index 3f206d5..ab5f399 100644 --- a/docs/reference/panel_empirical_bootstrap.html +++ b/docs/reference/panel_empirical_bootstrap.html @@ -1,9 +1,9 @@ -panel_empirical_bootstrap — panel_empirical_bootstrap • ptepanel_empirical_bootstrap — panel_empirical_bootstrap • ptetools - +
    @@ -28,14 +28,14 @@
    - +
    @@ -63,15 +63,43 @@

    panel_empirical_bootstrap

    Arguments

    -
    attgt.list
    + + +
    attgt.list

    list of attgt results from compute.pte

    -
    ptep
    +
    ptep

    pte_params object

    -
    subset_fun
    +
    setup_pte_fun
    +

    This is a function that should take in data, +yname (the name of the outcome variable in data), +gname (the name of the group variable), +idname (the name of the id variable), +and possibly other arguments such as the significance level alp, +the number of bootstrap iterations biters, and how many clusters +for parallel computing in the bootstrap cl. The key thing that +needs to be figured out in this function is which groups and time periods +ATT(g,t) should be computed in. The function should +return a pte_params object which contains all of the parameters +passed into the function as well as glist and tlist which +should be ordered lists of groups and time periods for ATT(g,t) to be computed.

    +

    This function provides also provides a good place for error handling related +to the types of data that can be handled.

    +

    The pte package contains the function setup_pte that is +a lightweight function that basically just takes the data, omits +the never-treated group from glist but includes all other groups +and drops the first time period. This works in cases where ATT would +be identified in the 2x2 case (i.e., where there are two time periods, +no units are treated in the first period and the identification strategy +"works" with access to a treated and untreated group and untreated +potential outcomes for both groups in the first period) — for example, +this approach works if DID is the identification strategy.

    + + +
    subset_fun

    This is a function that should take in data, g (for group), tp (for time period), and ... and be able to return the appropriate data.frame that can be used @@ -81,7 +109,7 @@

    Arguments

    belongs to, etc.

    -
    attgt_fun
    +
    attgt_fun

    This is a function that should work in the case where there is a single group and the "right" number of time periods to recover an estimate of the ATT. For example, in the contest of @@ -109,7 +137,16 @@

    Arguments

    substantially) computationally slower.

    -
    ...
    +
    extra_gt_returns
    +

    A place to return anything extra from particular +group-time average treatment effect calculations. For DID, this might +be something like propensity score estimates, regressions of untreated +potential outcomes on covariates. For ife, this could be something +like the first step regression 2sls estimates. This argument is also +potentially useful for debugging.

    + + +
    ...

    extra arguments that can be passed to create the correct subsets of the data (depending on subset_fun), to estimate group time average treatment effects (depending on attgt_fun), or to @@ -119,9 +156,7 @@

    Arguments

    Value

    - - -

    pte_emp_boot object

    +

    pte_emp_boot object

    @@ -136,15 +171,15 @@

    Value

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/print.group_time_att.html b/docs/reference/print.group_time_att.html index 5da07c8..49d3ed3 100644 --- a/docs/reference/print.group_time_att.html +++ b/docs/reference/print.group_time_att.html @@ -1,9 +1,9 @@ -print.group_time_att — print.group_time_att • pteprint.group_time_att — print.group_time_att • ptetools - +
    @@ -28,14 +28,14 @@
    - +
    @@ -50,17 +50,19 @@

    print.group_time_att

    - 
    # S3 method for group_time_att
+    
    # S3 method for class 'group_time_att'
 print(x, ...)

    Arguments

    -
    x
    + + +
    x

    a group_time_att object

    -
    ...
    +
    ...

    extra arguments

    @@ -77,15 +79,15 @@

    Arguments

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/print.pte_results.html b/docs/reference/print.pte_results.html index 2b8534f..c2ce115 100644 --- a/docs/reference/print.pte_results.html +++ b/docs/reference/print.pte_results.html @@ -1,9 +1,9 @@ -print.pte_results — print.pte_results • pteprint.pte_results — print.pte_results • ptetools - +
    @@ -28,14 +28,14 @@
    - +
    @@ -50,17 +50,19 @@

    print.pte_results

    - 
    # S3 method for pte_results
+    
    # S3 method for class 'pte_results'
 print(x, ...)

    Arguments

    -
    x
    + + +
    x

    a pte_results object

    -
    ...
    +
    ...

    extra arguments

    @@ -77,15 +79,15 @@

    Arguments

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/print.summary.dose_obj.html b/docs/reference/print.summary.dose_obj.html new file mode 100644 index 0000000..fde6c0d --- /dev/null +++ b/docs/reference/print.summary.dose_obj.html @@ -0,0 +1,93 @@ + +print.summary.dose_obj — print.summary.dose_obj • ptetools + + +
    +
    + + + +
    +
    +
    +

    print.summary.dose_obj

    + Source: R/process_dose_gt.R + +
    + +
    +

    prints a summary of a dose_obj object

    +
    + +
    + 
    # S3 method for class 'summary.dose_obj'
+print(x, ...)
    +
    + +
    +

    Arguments

    + + +
    x
    +

    a list containing the summary of a dose_obj object

    + + +
    ...
    +

    extra arguments

    + +
    + +
    + +
    + + +
    +

    Developed by Brantly Callaway.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/print.summary.pte_results.html b/docs/reference/print.summary.pte_results.html index 0c6c565..ff0d23d 100644 --- a/docs/reference/print.summary.pte_results.html +++ b/docs/reference/print.summary.pte_results.html @@ -1,9 +1,9 @@ -print.summary.pte_results — print.summary.pte_results • pteprint.summary.pte_results — print.summary.pte_results • ptetools - +
    @@ -28,14 +28,14 @@
    - +
    @@ -50,17 +50,19 @@

    print.summary.pte_results

    - 
    # S3 method for summary.pte_results
+    
    # S3 method for class 'summary.pte_results'
 print(x, ...)

    Arguments

    -
    x
    + + +
    x

    a summary.pte_results object

    -
    ...
    +
    ...

    extra arguments

    @@ -77,15 +79,15 @@

    Arguments

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/process_att_gt.html b/docs/reference/process_att_gt.html index 6256484..41e0734 100644 --- a/docs/reference/process_att_gt.html +++ b/docs/reference/process_att_gt.html @@ -1,9 +1,9 @@ -process_att_gt — process_att_gt • pteprocess_att_gt — process_att_gt • ptetools - +
    @@ -28,14 +28,14 @@
    - +
    @@ -55,11 +55,13 @@

    process_att_gt

    Arguments

    -
    att_gt_results
    + + +
    att_gt_results

    ATT(g,t)'s

    -
    ptep
    +
    ptep

    pte_params object

    @@ -76,15 +78,15 @@

    Arguments

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/pte.html b/docs/reference/pte.html index a7f7f43..e26bb4a 100644 --- a/docs/reference/pte.html +++ b/docs/reference/pte.html @@ -1,10 +1,10 @@ -Panel Treatment Effects — pte • ptePanel Treatment Effects — pte • ptetools - +
    @@ -29,14 +29,14 @@
    - +
    @@ -47,7 +47,7 @@

    Panel Treatment Effects

    -

    Tools for estimating treatment effects with panel data

    +

    Tools for estimating treatment effects with panel data.

    Main function for computing panel treatment effects

    @@ -64,37 +64,40 @@

    Panel Treatment Effects

    cband = TRUE, alp = 0.05, boot_type = "multiplier", - gt_type = "att", - ret_quantile = NULL, + weightsname = NULL, biters = 100, cl = 1, + gt_type = "att", + ret_quantile = NULL, ... )

    Arguments

    -
    yname
    + + +
    yname

    Name of outcome in data

    -
    gname
    +
    gname

    Name of group in data

    -
    tname
    +
    tname

    Name of time period in data

    -
    idname
    +
    idname

    Name of id in data

    -
    data
    +
    data

    balanced panel data

    -
    setup_pte_fun
    +
    setup_pte_fun

    This is a function that should take in data, yname (the name of the outcome variable in data), gname (the name of the group variable), @@ -116,11 +119,11 @@

    Arguments

    be identified in the 2x2 case (i.e., where there are two time periods, no units are treated in the first period and the identification strategy "works" with access to a treated and untreated group and untreated -potential outcomes for both groups in the first period) --- for example, +potential outcomes for both groups in the first period) — for example, this approach works if DID is the identification strategy.

    -
    subset_fun
    +
    subset_fun

    This is a function that should take in data, g (for group), tp (for time period), and ... and be able to return the appropriate data.frame that can be used @@ -130,7 +133,7 @@

    Arguments

    belongs to, etc.

    -
    attgt_fun
    +
    attgt_fun

    This is a function that should work in the case where there is a single group and the "right" number of time periods to recover an estimate of the ATT. For example, in the contest of @@ -158,11 +161,16 @@

    Arguments

    substantially) computationally slower.

    -
    alp
    +
    cband
    +

    whether or not to report a uniform (instead of pointwise) +confidence band (default is TRUE)

    + + +
    alp

    significance level; default is 0.05

    -
    boot_type
    +
    boot_type

    should be one of "multiplier" (the default) or "empirical". The multiplier bootstrap is generally much faster, but attgt_fun needs to provide an expression for the influence function (which could be challenging @@ -171,7 +179,20 @@

    Arguments

    parameter.

    -
    gt_type
    +
    weightsname
    +

    The name of the column that contains sampling weights. +The defaul is NULL, in which case no sampling weights are used.

    + + +
    biters
    +

    number of bootstrap iterations; default is 100

    + + +
    cl
    +

    number of clusters to be used when bootstrapping; default is 1

    + + +
    gt_type

    is the type of result that is computed for each group and time period. The default choice is "att" is this is (by far) the most common choice. The other option is "dtt", which stands for distribution @@ -181,15 +202,13 @@

    Arguments

    will often need to be provided in this case.

    -
    biters
    -

    number of bootstrap iterations; default is 100

    - - -
    cl
    -

    number of clusters to be used when bootstrapping; default is 1

    +
    ret_quantile
    +

    For functions that compute quantile treatment effects, +this is a specific quantile at which to report results, e.g., +ret_quantile = 0.5 will return that the qte at the median.

    -
    ...
    +
    ...

    extra arguments that can be passed to create the correct subsets of the data (depending on subset_fun), to estimate group time average treatment effects (depending on attgt_fun), or to @@ -199,9 +218,16 @@

    Arguments

    Value

    - - -

    pte_results object

    +

    pte_results object

    +
    +
    +

    See also

    +

    Useful links:

    +
    +
    +

    Author

    +

    Maintainer: Brantly Callaway brantly.callaway@uga.edu

    @@ -216,15 +242,15 @@

    Value

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/pte2.html b/docs/reference/pte2.html index 4019fb7..83038c7 100644 --- a/docs/reference/pte2.html +++ b/docs/reference/pte2.html @@ -1,9 +1,9 @@ -pte2 — pte2 • ptepte2 — pte2 • ptetools - +
    @@ -28,14 +28,14 @@
    - +
    @@ -62,7 +62,14 @@

    pte2

    cband = TRUE, alp = 0.05, boot_type = "multiplier", + weightsname = NULL, gt_type = "att", + ret_quantile = NULL, + global_fun = FALSE, + time_period_fun = FALSE, + group_fun = FALSE, + process_dtt_gt_fun = process_dtt_gt, + process_dose_gt_fun = process_dose_gt, biters = 100, cl = 1, ... @@ -71,27 +78,29 @@

    pte2

    Arguments

    -
    yname
    + + +
    yname

    Name of outcome in data

    -
    gname
    +
    gname

    Name of group in data

    -
    tname
    +
    tname

    Name of time period in data

    -
    idname
    +
    idname

    Name of id in data

    -
    data
    +
    data

    balanced panel data

    -
    setup_pte_fun
    +
    setup_pte_fun

    This is a function that should take in data, yname (the name of the outcome variable in data), gname (the name of the group variable), @@ -113,11 +122,11 @@

    Arguments

    be identified in the 2x2 case (i.e., where there are two time periods, no units are treated in the first period and the identification strategy "works" with access to a treated and untreated group and untreated -potential outcomes for both groups in the first period) --- for example, +potential outcomes for both groups in the first period) — for example, this approach works if DID is the identification strategy.

    -
    subset_fun
    +
    subset_fun

    This is a function that should take in data, g (for group), tp (for time period), and ... and be able to return the appropriate data.frame that can be used @@ -127,7 +136,7 @@

    Arguments

    belongs to, etc.

    -
    attgt_fun
    +
    attgt_fun

    This is a function that should work in the case where there is a single group and the "right" number of time periods to recover an estimate of the ATT. For example, in the contest of @@ -155,11 +164,16 @@

    Arguments

    substantially) computationally slower.

    -
    alp
    +
    cband
    +

    whether or not to report a uniform (instead of pointwise) +confidence band (default is TRUE)

    + + +
    alp

    significance level; default is 0.05

    -
    boot_type
    +
    boot_type

    should be one of "multiplier" (the default) or "empirical". The multiplier bootstrap is generally much faster, but attgt_fun needs to provide an expression for the influence function (which could be challenging @@ -168,32 +182,76 @@

    Arguments

    parameter.

    -
    gt_type
    +
    weightsname
    +

    The name of the column that contains sampling weights. +The defaul is NULL, in which case no sampling weights are used.

    + + +
    gt_type

    which type of group-time effects are computed. -For backward compatiblity, the default choice is "att"

    +The default is "att". Different estimation strategies can implement +their own choices for gt_type

    + + +
    ret_quantile
    +

    For functions that compute quantile treatment effects, +this is a specific quantile at which to report results, e.g., +ret_quantile = 0.5 will return that the qte at the median.

    + +
    global_fun
    +

    Logical indicating whether or not untreated potential +outcomes can be estimated in one shot, i.e., for all groups and time periods. +Main use case would be for one-shot imputation estimators. Not supported yet.

    -
    biters
    + +
    time_period_fun
    +

    Logical indicating whether or not untreated potential +outcomes can be estimated for all groups in the same time period. Not supported yet.

    + + +
    group_fun
    +

    Logical indicating whether or not untreated potential outcomes +can be estimated for all time periods for a single group. Not supported yet. +These functions aim at reducing or eliminating running the same code multiple times.

    + + +
    process_dtt_gt_fun
    +

    An optional function to customize results when +the gt-specific function returns the distribution of treated and untreated +potential outcomes. The default is process_dtt_gt, which is a function +provided by the package. See that function for an example of what this function +should return. This is unused is unused except in cases where +the results involve distributions.

    + + +
    biters

    number of bootstrap iterations; default is 100

    -
    cl
    +
    cl

    number of clusters to be used when bootstrapping; default is 1

    -
    ...
    +
    ...

    extra arguments that can be passed to create the correct subsets of the data (depending on subset_fun), to estimate group time average treatment effects (depending on attgt_fun), or to aggregating treatment effects (particularly useful are min_e, max_e, and balance_e arguments to event study aggregations)

    + +
    process_dose
    +

    An optional function to customize results when the gt-specific +function returns treatment effects that depend on dose (i.e., amount of the +treatment). The default is process_dose_gt, which is a function provided +by the package. See that function for an example of what this function should +return. This is unused except in cases where the results involve doses.

    +

    Value

    - - -

    pte_results object

    +

    pte_results object

    @@ -208,15 +266,15 @@

    Value

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/pte_aggte.html b/docs/reference/pte_aggte.html index 7e14b6e..3452257 100644 --- a/docs/reference/pte_aggte.html +++ b/docs/reference/pte_aggte.html @@ -1,27 +1,15 @@ -pte_aggte - -This is a slight edit of the aggte function from the did package. -Currently, it only provides aggregations for "overall" treatment effects -and event studies. It also will provide the weights directly which is -currently used for constructing aggregations based on distributions. -The other difference is that, pte_aggte provides inference results -where the only randomness is coming from the outcomes (not from the group -assignment nor from the covariates). — pte_aggte • pte - +
    @@ -46,34 +34,25 @@
    - +
    -

    pte_aggte - -This is a slight edit of the aggte function from the did package. -Currently, it only provides aggregations for "overall" treatment effects -and event studies. It also will provide the weights directly which is -currently used for constructing aggregations based on distributions. -The other difference is that, pte_aggte provides inference results -where the only randomness is coming from the outcomes (not from the group -assignment nor from the covariates).

    +

    pte_aggte

    Source: R/pte_aggte.R
    -

    pte_aggte

    -

    This is a slight edit of the aggte function from the did package. +

    This is a slight edit of the aggte function from the did package. Currently, it only provides aggregations for "overall" treatment effects and event studies. It also will provide the weights directly which is currently used for constructing aggregations based on distributions. @@ -83,9 +62,28 @@

    pte_aggte

    - 
    pte_aggte(attgt, type = "overall")
    + 
    pte_aggte(
+  attgt,
+  type = "overall",
+  balance_e = NULL,
+  min_e = -Inf,
+  max_e = Inf,
+  ...
+)
    +
    +

    Arguments

    + + +
    attgt
    +

    A group_time_att object to be aggregated

    + + +
    type
    +

    The type of aggregation to be done. Default is "overall"

    + +
    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/pte_attgt.html b/docs/reference/pte_attgt.html index 7b1082f..3975240 100644 --- a/docs/reference/pte_attgt.html +++ b/docs/reference/pte_attgt.html @@ -1,5 +1,5 @@ -pte_attgt — pte_attgt • pte - +
    @@ -38,14 +38,14 @@
    - +
    @@ -65,7 +65,7 @@

    pte_attgt

    G (group identifier), period (time period), name (equal to "pre" for pre-treatment periods and equal to "post" for post treatment periods), Y (outcome).

    -

    In our case, we call pte::two_by_two_subset which sets up the +

    In our case, we call pte::two_by_two_subset which sets up the data to have this format before the call to pte_attgt

    @@ -83,46 +83,46 @@

    pte_attgt

    Arguments

    -
    gt_data
    + + +
    gt_data

    data that is "local" to a particular group-time average treatment effect

    -
    xformla
    +
    xformla

    one-sided formula for covariates used in the propensity score and outcome regression models

    -
    d_outcome
    +
    d_outcome

    Whether or not to take the first difference of the outcome. The default is FALSE. To use difference-in-differences, set this to be TRUE.

    -
    d_covs_formula
    +
    d_covs_formula

    A formula for time varying covariates to enter the first estimation step models. The default is not to include any, and, hence, to only include pre-treatment covariats.

    -
    lagged_outcome_cov
    +
    lagged_outcome_cov

    Whether to include the lagged outcome as a covariate. Default is FALSE.

    -
    est_method
    +
    est_method

    Which type of estimation method to use. Default is "dr" for doubly robust. The other option is "reg" for regression adjustment.

    -
    ...
    +
    ...

    extra function arguments; not used here

    Value

    - - -

    attgt_if

    +

    attgt_if

    @@ -137,15 +137,15 @@

    Value

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/pte_default.html b/docs/reference/pte_default.html index 63095fb..aa13baa 100644 --- a/docs/reference/pte_default.html +++ b/docs/reference/pte_default.html @@ -1,12 +1,12 @@ -pte_default — pte_default • ptepte_default — pte_default • ptetools - +
    @@ -31,14 +31,14 @@
    - +
    @@ -68,6 +68,9 @@

    pte_default

    lagged_outcome_cov = FALSE, est_method = "dr", anticipation = 0, + base_period = "varying", + control_group = "notyettreated", + weightsname = NULL, cband = TRUE, alp = 0.05, boot_type = "multiplier", @@ -78,57 +81,93 @@

    pte_default

    Arguments

    -
    yname
    + + +
    yname

    Name of outcome in data

    -
    gname
    +
    gname

    Name of group in data

    -
    tname
    +
    tname

    Name of time period in data

    -
    idname
    +
    idname

    Name of id in data

    -
    data
    +
    data

    balanced panel data

    -
    xformla
    +
    xformla

    one-sided formula for covariates used in the propensity score and outcome regression models

    -
    d_outcome
    +
    d_outcome

    Whether or not to take the first difference of the outcome. The default is FALSE. To use difference-in-differences, set this to be TRUE.

    -
    d_covs_formula
    +
    d_covs_formula

    A formula for time varying covariates to enter the first estimation step models. The default is not to include any, and, hence, to only include pre-treatment covariats.

    -
    lagged_outcome_cov
    +
    lagged_outcome_cov

    Whether to include the lagged outcome as a covariate. Default is FALSE.

    -
    est_method
    +
    est_method

    Which type of estimation method to use. Default is "dr" for doubly robust. The other option is "reg" for regression adjustment.

    -
    alp
    +
    anticipation
    +

    how many periods before the treatment actually takes +place that it can have an effect on outcomes

    + + +
    base_period
    +

    The type of base period to use. This only affects +the numeric value of results in pre-treatment periods. Results in +post-treatment periods are not affected by this choice. The default +is "varying", where the base period will "back up" to the immediately +preceding period in pre-treatment periods. The other option is "universal" +where the base period is fixed in pre-treatment periods to be the period +right before the treatment starts. "Universal" is commonly used in +difference-in-differences applications, but can be unnatural for other +identification strategies.

    + + +
    control_group
    +

    Which group is used as the comparison group. +The default choice is "notyettreated", but +different estimation strategies can implement their own choices +for the control group

    + + +
    weightsname
    +

    The name of the column that contains sampling weights. +The defaul is NULL, in which case no sampling weights are used.

    + + +
    cband
    +

    whether or not to report a uniform (instead of pointwise) +confidence band (default is TRUE)

    + + +
    alp

    significance level; default is 0.05

    -
    boot_type
    +
    boot_type

    should be one of "multiplier" (the default) or "empirical". The multiplier bootstrap is generally much faster, but attgt_fun needs to provide an expression for the influence function (which could be challenging @@ -137,19 +176,17 @@

    Arguments

    parameter.

    -
    biters
    +
    biters

    number of bootstrap iterations; default is 100

    -
    cl
    +
    cl

    number of clusters to be used when bootstrapping; default is 1

    Value

    - - -

    pte_results object

    +

    pte_results object

    @@ -164,15 +201,15 @@

    Value

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/pte_dose_results.html b/docs/reference/pte_dose_results.html new file mode 100644 index 0000000..b79af8c --- /dev/null +++ b/docs/reference/pte_dose_results.html @@ -0,0 +1,100 @@ + +pte_dose_results — pte_dose_results • ptetools + + +
    +
    + + + +
    +
    +
    +

    pte_dose_results

    + Source: R/classes.R + +
    + +
    +

    class for holding pte results

    +
    + +
    + 
    pte_dose_results(att_gt, dose, att_d = NULL, acrt_d = NULL, ptep)
    +
    + +
    +

    Arguments

    + + +
    att_gt
    +

    attgt results

    + + +
    dose
    +

    vector of doses

    + + +
    att_d
    +

    ATT(d) for each value of dose

    + + +
    acrt_d
    +

    ACRT(d) for each value of dose

    + +
    + +
    + +
    + + +
    +

    Developed by Brantly Callaway.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/pte_emp_boot.html b/docs/reference/pte_emp_boot.html index ab1b568..f4f1b50 100644 --- a/docs/reference/pte_emp_boot.html +++ b/docs/reference/pte_emp_boot.html @@ -1,10 +1,10 @@ -pte_emp_boot — pte_emp_boot • ptepte_emp_boot — pte_emp_boot • ptetools - +
    @@ -29,14 +29,14 @@
    - +
    @@ -66,38 +66,52 @@

    pte_emp_boot

    Arguments

    -
    attgt_results
    + + +
    attgt_results

    data.frame holding attgt results

    -
    overall_results
    +
    overall_results

    data.frame holding overall results

    -
    group_results
    +
    group_results

    data.frame holding group results

    -
    dyn_results
    +
    dyn_results

    data.frame holding dynamic results

    -
    overall_weights
    +
    overall_weights

    vector containing weights on underlying ATT(g,t) for overall treatment effect parameter

    -
    dyn_weights
    +
    dyn_weights

    list containing weights on underlying ATT(g,t) for each value of e corresponding to the dynamic treatment effect parameters.

    + +
    group_weights
    +

    list containing weights on underlying ATT(g,t) +corresponding to deliver averaged group-specific treatment effects

    + + +
    extra_gt_returns
    +

    A place to return anything extra from particular +group-time average treatment effect calculations. For DID, this might +be something like propensity score estimates, regressions of untreated +potential outcomes on covariates. For ife, this could be something +like the first step regression 2sls estimates. This argument is also +potentially useful for debugging.

    +

    Value

    - - -

    pte_emp_boot object

    +

    pte_emp_boot object

    @@ -112,15 +126,15 @@

    Value

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/pte_params.html b/docs/reference/pte_params.html index d167ddd..3861113 100644 --- a/docs/reference/pte_params.html +++ b/docs/reference/pte_params.html @@ -1,9 +1,9 @@ -pte_params — pte_params • ptepte_params — pte_params • ptetools - +
    @@ -28,14 +28,14 @@
    - +
    @@ -61,8 +61,15 @@

    pte_params

    cband, alp, boot_type, + anticipation = NULL, + base_period = NULL, + weightsname = NULL, + control_group = "notyettreated", gt_type = "att", ret_quantile = 0.5, + global_fun = FALSE, + time_period_fun = FALSE, + group_fun = FALSE, biters, cl )
    @@ -70,54 +77,114 @@

    pte_params

    Arguments

    -
    yname
    + + +
    yname

    Name of outcome in data

    -
    gname
    +
    gname

    Name of group in data

    -
    tname
    +
    tname

    Name of time period in data

    -
    idname
    +
    idname

    Name of id in data

    -
    data
    +
    data

    balanced panel data

    -
    glist
    +
    glist

    list of groups to create group-time average treatment effects for

    -
    tlist
    +
    tlist

    list of time periods to create group-time average treatment effects for

    -
    alp
    +
    cband
    +

    whether or not to report a uniform (instead of pointwise) +confidence band (default is TRUE)

    + + +
    alp

    significance level; default is 0.05

    -
    boot_type
    +
    boot_type

    which type of bootstrap to use

    -
    gt_type
    +
    anticipation
    +

    how many periods before the treatment actually takes +place that it can have an effect on outcomes

    + + +
    base_period
    +

    The type of base period to use. This only affects +the numeric value of results in pre-treatment periods. Results in +post-treatment periods are not affected by this choice. The default +is "varying", where the base period will "back up" to the immediately +preceding period in pre-treatment periods. The other option is "universal" +where the base period is fixed in pre-treatment periods to be the period +right before the treatment starts. "Universal" is commonly used in +difference-in-differences applications, but can be unnatural for other +identification strategies.

    + + +
    weightsname
    +

    The name of the column that contains sampling weights. +The defaul is NULL, in which case no sampling weights are used.

    + + +
    control_group
    +

    Which group is used as the comparison group. +The default choice is "notyettreated", but +different estimation strategies can implement their own choices +for the control group

    + + +
    gt_type

    which type of group-time effects are computed. -For backward compatiblity, the default choice is "att"

    +The default is "att". Different estimation strategies can implement +their own choices for gt_type

    + + +
    ret_quantile
    +

    For functions that compute quantile treatment effects, +this is a specific quantile at which to report results, e.g., +ret_quantile = 0.5 will return that the qte at the median.

    + + +
    global_fun
    +

    Logical indicating whether or not untreated potential +outcomes can be estimated in one shot, i.e., for all groups and time periods. +Main use case would be for one-shot imputation estimators. Not supported yet.

    -
    biters
    +
    time_period_fun
    +

    Logical indicating whether or not untreated potential +outcomes can be estimated for all groups in the same time period. Not supported yet.

    + + +
    group_fun
    +

    Logical indicating whether or not untreated potential outcomes +can be estimated for all time periods for a single group. Not supported yet. +These functions aim at reducing or eliminating running the same code multiple times.

    + + +
    biters

    number of bootstrap iterations; default is 100

    -
    cl
    +
    cl

    number of clusters to be used when bootstrapping; default is 1

    @@ -134,15 +201,15 @@

    Arguments

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/pte_results.html b/docs/reference/pte_results.html index 41225da..f5f75af 100644 --- a/docs/reference/pte_results.html +++ b/docs/reference/pte_results.html @@ -1,9 +1,9 @@ -pte_results — pte_results • ptepte_results — pte_results • ptetools - +
    @@ -28,14 +28,14 @@
    - +
    @@ -55,19 +55,21 @@

    pte_results

    Arguments

    -
    att_gt
    + + +
    att_gt

    attgt results

    -
    overall_att
    +
    overall_att

    overall_att results

    -
    event_study
    +
    event_study

    event_study results

    -
    ptep
    +
    ptep

    pte_params object

    @@ -84,15 +86,15 @@

    Arguments

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/qott_pte_aggregations.html b/docs/reference/qott_pte_aggregations.html index d3cd81e..1e286a8 100644 --- a/docs/reference/qott_pte_aggregations.html +++ b/docs/reference/qott_pte_aggregations.html @@ -1,10 +1,10 @@ -qott_pte_aggregations — qott_pte_aggregations • pteqott_pte_aggregations — qott_pte_aggregations • ptetools - +
    @@ -29,14 +29,14 @@
    - +
    @@ -57,19 +57,28 @@

    qott_pte_aggregations

    Arguments

    -
    attgt.list
    + + +
    attgt.list

    list of attgt results from compute.pte

    -
    ptep
    +
    ptep

    pte_params object

    + +
    extra_gt_returns
    +

    A place to return anything extra from particular +group-time average treatment effect calculations. For DID, this might +be something like propensity score estimates, regressions of untreated +potential outcomes on covariates. For ife, this could be something +like the first step regression 2sls estimates. This argument is also +potentially useful for debugging.

    +

    Value

    - - -

    pte_emp_boot object

    +

    pte_emp_boot object

    @@ -84,15 +93,15 @@

    Value

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/qtt_pte_aggregations.html b/docs/reference/qtt_pte_aggregations.html index d6b26ef..20ab383 100644 --- a/docs/reference/qtt_pte_aggregations.html +++ b/docs/reference/qtt_pte_aggregations.html @@ -1,10 +1,10 @@ -qtt_pte_aggregations — qtt_pte_aggregations • pteqtt_pte_aggregations — qtt_pte_aggregations • ptetools - +
    @@ -29,14 +29,14 @@
    - +
    @@ -57,19 +57,28 @@

    qtt_pte_aggregations

    Arguments

    -
    attgt.list
    + + +
    attgt.list

    list of attgt results from compute.pte

    -
    ptep
    +
    ptep

    pte_params object

    + +
    extra_gt_returns
    +

    A place to return anything extra from particular +group-time average treatment effect calculations. For DID, this might +be something like propensity score estimates, regressions of untreated +potential outcomes on covariates. For ife, this could be something +like the first step regression 2sls estimates. This argument is also +potentially useful for debugging.

    +

    Value

    - - -

    pte_emp_boot object

    +

    pte_emp_boot object

    @@ -84,15 +93,15 @@

    Value

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/setup_pte.html b/docs/reference/setup_pte.html index 5f43d28..4c09213 100644 --- a/docs/reference/setup_pte.html +++ b/docs/reference/setup_pte.html @@ -1,14 +1,14 @@ -Setup panel treatment effects parameters — setup_pte • pteSetup panel treatment effects parameters — setup_pte • ptetools - +
    @@ -33,14 +33,14 @@
    - +
    @@ -68,9 +68,11 @@

    Setup panel treatment effects parameters

    data, required_pre_periods = 1, anticipation = 0, + base_period = "varying", cband = TRUE, alp = 0.05, boot_type = "multiplier", + weightsname = NULL, gt_type = "att", ret_quantile = 0.5, biters = 100, @@ -79,11 +81,97 @@

    Setup panel treatment effects parameters

    )
    +
    +

    Arguments

    + + +
    yname
    +

    Name of outcome in data

    + + +
    gname
    +

    Name of group in data

    + + +
    tname
    +

    Name of time period in data

    + + +
    idname
    +

    Name of id in data

    + + +
    data
    +

    balanced panel data

    + + +
    required_pre_periods
    +

    The number of required pre-treatment periods to implement +the estimation strategy. Default is 1.

    + + +
    anticipation
    +

    how many periods before the treatment actually takes +place that it can have an effect on outcomes

    + + +
    base_period
    +

    The type of base period to use. This only affects +the numeric value of results in pre-treatment periods. Results in +post-treatment periods are not affected by this choice. The default +is "varying", where the base period will "back up" to the immediately +preceding period in pre-treatment periods. The other option is "universal" +where the base period is fixed in pre-treatment periods to be the period +right before the treatment starts. "Universal" is commonly used in +difference-in-differences applications, but can be unnatural for other +identification strategies.

    + + +
    cband
    +

    whether or not to report a uniform (instead of pointwise) +confidence band (default is TRUE)

    + + +
    alp
    +

    significance level; default is 0.05

    + + +
    boot_type
    +

    which type of bootstrap to use

    + + +
    weightsname
    +

    The name of the column that contains sampling weights. +The defaul is NULL, in which case no sampling weights are used.

    + + +
    gt_type
    +

    which type of group-time effects are computed. +The default is "att". Different estimation strategies can implement +their own choices for gt_type

    + + +
    ret_quantile
    +

    For functions that compute quantile treatment effects, +this is a specific quantile at which to report results, e.g., +ret_quantile = 0.5 will return that the qte at the median.

    + + +
    biters
    +

    number of bootstrap iterations; default is 100

    + + +
    cl
    +

    number of clusters to be used when bootstrapping; default is 1

    + + +
    ...
    +

    additional arguments

    + +

    Value

    - - -

    pte_params object

    +

    pte_params object

    @@ -98,15 +186,15 @@

    Value

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/setup_pte_basic.html b/docs/reference/setup_pte_basic.html index 4b8a30b..9366f8a 100644 --- a/docs/reference/setup_pte_basic.html +++ b/docs/reference/setup_pte_basic.html @@ -1,12 +1,12 @@ -Example setup panel treatment effects parameters — setup_pte_basic • pteExample setup panel treatment effects parameters — setup_pte_basic • ptetools - +
    @@ -43,14 +43,14 @@
    - +
    @@ -68,7 +68,7 @@

    Example setup panel treatment effects parameters

    that is computed by this function is the list of groups and list of time periods where ATT(g,t) should be computed. In particular, this function omits the never-treated group but includes all other groups and drops the first -time period. This setup is basically geared towards the 2x2 case --- +time period. This setup is basically geared towards the 2x2 case — i.e., where ATT could be identified with two periods, a treated and untreated group, and the first period being pre-treatment for both groups. This is the relevant case for DID, but is also relevant for other cases as well. @@ -99,52 +99,68 @@

    Example setup panel treatment effects parameters

    Arguments

    -
    yname
    + + +
    yname

    Name of outcome in data

    -
    gname
    +
    gname

    Name of group in data

    -
    tname
    +
    tname

    Name of time period in data

    -
    idname
    +
    idname

    Name of id in data

    -
    data
    +
    data

    balanced panel data

    -
    alp
    +
    cband
    +

    whether or not to report a uniform (instead of pointwise) +confidence band (default is TRUE)

    + + +
    alp

    significance level; default is 0.05

    -
    boot_type
    +
    boot_type

    which type of bootstrap to use

    -
    gt_type
    +
    gt_type

    which type of group-time effects are computed. -For backward compatiblity, the default choice is "att"

    +The default is "att". Different estimation strategies can implement +their own choices for gt_type

    -
    biters
    +
    ret_quantile
    +

    For functions that compute quantile treatment effects, +this is a specific quantile at which to report results, e.g., +ret_quantile = 0.5 will return that the qte at the median.

    + + +
    biters

    number of bootstrap iterations; default is 100

    -
    cl
    +
    cl

    number of clusters to be used when bootstrapping; default is 1

    + +
    ...
    +

    additional arguments

    +

    Value

    - - -

    pte_params object

    +

    pte_params object

    @@ -159,15 +175,15 @@

    Value

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/summary.aggte_obj.html b/docs/reference/summary.aggte_obj.html new file mode 100644 index 0000000..cb2b8c7 --- /dev/null +++ b/docs/reference/summary.aggte_obj.html @@ -0,0 +1,93 @@ + +Summary Aggregate Treatment Effect Parameter Objects — summary.aggte_obj • ptetools + + +
    +
    + + + +
    +
    +
    +

    Summary Aggregate Treatment Effect Parameter Objects

    + Source: R/pte_aggte.R + +
    + +
    +

    A function to summarize aggregated treatment effect parameters.

    +
    + +
    + 
    # S3 method for class 'aggte_obj'
+summary(object, ...)
    +
    + +
    +

    Arguments

    + + +
    object
    +

    an aggte_obj object

    + + +
    ...
    +

    other arguments

    + +
    + +
    + +
    + + +
    +

    Developed by Brantly Callaway.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/summary.dose_obj.html b/docs/reference/summary.dose_obj.html new file mode 100644 index 0000000..a25a8dc --- /dev/null +++ b/docs/reference/summary.dose_obj.html @@ -0,0 +1,93 @@ + +summary.dose_obj — summary.dose_obj • ptetools + + +
    +
    + + + +
    +
    +
    +

    summary.dose_obj

    + Source: R/process_dose_gt.R + +
    + +
    +

    summarizes a dose_obj object

    +
    + +
    + 
    # S3 method for class 'dose_obj'
+summary(object, ...)
    +
    + +
    +

    Arguments

    + + +
    object
    +

    an dose_obj object

    + + +
    ...
    +

    extra arguments

    + +
    + +
    + +
    + + +
    +

    Developed by Brantly Callaway.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/summary.group_time_att.html b/docs/reference/summary.group_time_att.html index e385ad5..2bfd22e 100644 --- a/docs/reference/summary.group_time_att.html +++ b/docs/reference/summary.group_time_att.html @@ -1,9 +1,9 @@ -summary.group_time_att — summary.group_time_att • ptesummary.group_time_att — summary.group_time_att • ptetools - +
    @@ -28,14 +28,14 @@
    - +
    @@ -50,17 +50,19 @@

    summary.group_time_att

    - 
    # S3 method for group_time_att
+    
    # S3 method for class 'group_time_att'
 summary(object, ...)

    Arguments

    -
    object
    + + +
    object

    an group_time_att object

    -
    ...
    +
    ...

    extra arguments

    @@ -77,15 +79,15 @@

    Arguments

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/summary.pte_emp_boot.html b/docs/reference/summary.pte_emp_boot.html index a346ac6..7789192 100644 --- a/docs/reference/summary.pte_emp_boot.html +++ b/docs/reference/summary.pte_emp_boot.html @@ -1,9 +1,9 @@ -summary.pte_emp_boot — summary.pte_emp_boot • ptesummary.pte_emp_boot — summary.pte_emp_boot • ptetools - +
    @@ -28,14 +28,14 @@
    - +
    @@ -50,25 +50,25 @@

    summary.pte_emp_boot

    - 
    # S3 method for pte_emp_boot
+    
    # S3 method for class 'pte_emp_boot'
 summary(object, ...)

    Arguments

    -
    object
    + + +
    object

    a pte_emp_boot object

    -
    ...
    +
    ...

    additional function arguments

    Value

    - - -

    summary.pte_results object

    +

    summary.pte_results object

    @@ -83,15 +83,15 @@

    Value

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/summary.pte_results.html b/docs/reference/summary.pte_results.html index 84b1a42..887d375 100644 --- a/docs/reference/summary.pte_results.html +++ b/docs/reference/summary.pte_results.html @@ -1,9 +1,9 @@ -summary.pte_results — summary.pte_results • ptesummary.pte_results — summary.pte_results • ptetools - +
    @@ -28,14 +28,14 @@
    - +
    @@ -50,17 +50,19 @@

    summary.pte_results

    - 
    # S3 method for pte_results
+    
    # S3 method for class 'pte_results'
 summary(object, ...)

    Arguments

    -
    object
    + + +
    object

    an pte_results object

    -
    ...
    +
    ...

    other arguments

    @@ -77,15 +79,15 @@

    Arguments

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/two_by_two_subset.html b/docs/reference/two_by_two_subset.html index b19a214..9ba2021 100644 --- a/docs/reference/two_by_two_subset.html +++ b/docs/reference/two_by_two_subset.html @@ -1,12 +1,12 @@ -two_by_two_subset — two_by_two_subset • ptetwo_by_two_subset — two_by_two_subset • ptetools - +
    @@ -31,14 +31,14 @@
    - +
    @@ -56,40 +56,64 @@

    two_by_two_subset

    - 
    two_by_two_subset(data, g, tp, control_group = "notyettreated", ...)
    + 
    two_by_two_subset(
+  data,
+  g,
+  tp,
+  control_group = "notyettreated",
+  anticipation = 0,
+  base_period = "varying",
+  ...
+)

    Arguments

    -
    data
    + + +
    data

    the full dataset

    -
    g
    +
    g

    the current group

    -
    tp
    +
    tp

    the current time period

    -
    control_group
    +
    control_group

    whether to use "notyettreated" (default) or "nevertreated"

    -
    ...
    +
    anticipation
    +

    the number of periods of anticipation (i.e., number +of periods before the treatment happens where the treatment can "already" +affect the outcome)

    + + +
    base_period
    +

    The type of base period to use. This only affects +the numeric value of results in pre-treatment periods. Results in +post-treatment periods are not affected by this choice. The default +is "varying", where the base period will "back up" to the immediately +preceding period in pre-treatment periods. The other option is "universal" +where the base period is fixed in pre-treatment periods to be the period +right before the treatment starts. "Universal" is commonly used in +difference-in-differences applications, but can be unnatural for other +identification strategies.

    + + +
    ...

    extra arguments to get the subset correct

    Value

    - - -

    list that contains correct subset of data, n1

    - - -

    number of observations +

    list that contains correct subset of data, n1 +number of observations in this subset, and disidx a vector of the correct ids for this subset.

    @@ -106,15 +130,15 @@

    Value

    -

    Site built with pkgdown 2.0.6.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/reference/wif.html b/docs/reference/wif.html new file mode 100644 index 0000000..90db938 --- /dev/null +++ b/docs/reference/wif.html @@ -0,0 +1,114 @@ + +Compute extra term in influence function due to estimating weights — wif • ptetools + + +
    +
    + + + +
    +
    +
    +

    Compute extra term in influence function due to estimating weights

    + Source: R/pte_aggte.R + +
    + +
    +

    A function to compute the extra term that shows up in the +influence function for aggregated treatment effect parameters +due to estimating the weights

    +
    + +
    + 
    wif(keepers, pg, weights.ind, G, group)
    +
    + +
    +

    Arguments

    + + +
    keepers
    +

    a vector of indices for which group-time average +treatment effects are used to compute a particular aggregated parameter

    + + +
    pg
    +

    a vector with same length as total number of group-time average +treatment effects that contains the probability of being in particular group

    + + +
    weights.ind
    +

    additional sampling weights (nx1)

    + + +
    G
    +

    vector containing which group a unit belongs to (nx1)

    + + +
    group
    +

    vector of groups

    + +
    +
    +

    Value

    +

    nxk influence function matrix

    +
    + +
    + +
    + + +
    +

    Developed by Brantly Callaway.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/site.webmanifest b/docs/site.webmanifest new file mode 100644 index 0000000..4ebda26 --- /dev/null +++ b/docs/site.webmanifest @@ -0,0 +1,21 @@ +{ + "name": "", + "short_name": "", + "icons": [ + { + "src": "/web-app-manifest-192x192.png", + "sizes": "192x192", + "type": "image/png", + "purpose": "maskable" + }, + { + "src": "/web-app-manifest-512x512.png", + "sizes": "512x512", + "type": "image/png", + "purpose": "maskable" + } + ], + "theme_color": "#ffffff", + "background_color": "#ffffff", + "display": "standalone" +} \ No newline at end of file diff --git a/docs/sitemap.xml b/docs/sitemap.xml index 26f5bc8..e8f4cc4 100644 --- a/docs/sitemap.xml +++ b/docs/sitemap.xml @@ -1,114 +1,54 @@ - - - - /404.html - - - /authors.html - - - /index.html - - - /reference/attgt_if.html - - - /reference/attgt_noif.html - - - /reference/attgt_pte_aggregations.html - - - /reference/compute.pte.html - - - /reference/compute.pte2.html - - - /reference/did_attgt.html - - - /reference/ggpte.html - - - /reference/group_time_att.html - - - /reference/gt_data_frame.html - - - /reference/index.html - - - /reference/mboot2.html - - - /reference/orig2t.html - - - /reference/panel_empirical_bootstrap.html - - - /reference/print.group_time_att.html - - - /reference/print.pte_results.html - - - /reference/print.summary.pte_results.html - - - /reference/process_att_gt.html - - - /reference/pte.html - - - /reference/pte2.html - - - /reference/pte_aggte.html - - - /reference/pte_attgt.html - - - /reference/pte_default.html - - - /reference/pte_emp_boot.html - - - /reference/pte_params.html - - - /reference/pte_results.html - - - /reference/qott_pte_aggregations.html - - - /reference/qtt_pte_aggregations.html - - - /reference/setup_pte.html - - - /reference/setup_pte_basic.html - - - /reference/summary.group_time_att.html - - - /reference/summary.pte_emp_boot.html - - - /reference/summary.pte_results.html - - - /reference/t2orig.html - - - /reference/two_by_two_subset.html - + +/404.html +/authors.html +/index.html +/reference/aggte_obj.html +/reference/attgt_if.html +/reference/attgt_noif.html +/reference/attgt_pte_aggregations.html +/reference/compute.pte.html +/reference/compute.pte2.html +/reference/crit_val_checks.html +/reference/did_attgt.html +/reference/dose_obj.html +/reference/getSE.html +/reference/get_agg_inf_func.html +/reference/ggpte.html +/reference/ggpte_cont.html +/reference/group_time_att.html +/reference/gt_data_frame.html +/reference/index.html +/reference/keep_all_pretreatment_subset.html +/reference/keep_all_untreated_subset.html +/reference/mboot2.html +/reference/orig2t.html +/reference/overall_weights.html +/reference/panel_empirical_bootstrap.html +/reference/print.group_time_att.html +/reference/print.pte_results.html +/reference/print.summary.dose_obj.html +/reference/print.summary.pte_results.html +/reference/process_att_gt.html +/reference/pte.html +/reference/pte2.html +/reference/pte_aggte.html +/reference/pte_attgt.html +/reference/pte_default.html +/reference/pte_dose_results.html +/reference/pte_emp_boot.html +/reference/pte_params.html +/reference/pte_results.html +/reference/qott_pte_aggregations.html +/reference/qtt_pte_aggregations.html +/reference/setup_pte.html +/reference/setup_pte_basic.html +/reference/summary.aggte_obj.html +/reference/summary.dose_obj.html +/reference/summary.group_time_att.html +/reference/summary.pte_emp_boot.html +/reference/summary.pte_results.html +/reference/t2orig.html +/reference/two_by_two_subset.html +/reference/wif.html + diff --git a/docs/web-app-manifest-192x192.png b/docs/web-app-manifest-192x192.png new file mode 100644 index 0000000000000000000000000000000000000000..d76b3a2bfab766d87f760cc3ffdc61282de8cd36 GIT binary patch literal 11626 zcmV-wEtS%VP)knB&sA-0Tp_064;n|_da~~JLk=eW(G+J zA!%l$d%y2~An9pl^xpaJ{m(i7Ik!a%H5z?Dtn&*(Z}qs~EJj2*dboPCpM%r+dG#pN zXwm~(wD=svI=(3k?S0AFA<5aN(qK0vXS*z}wS^uX9}4zoR6~t=9{?>r2fbhZPm8x{ zFS(X3$nZ6=+*2CbXOgq)7T4BF&i(;<4u3{;$Gd&q|%mm7HDn7`??A zSkY}N|L*~U&Q40Mje!{LF^G+QAlRQ@4K?a)_`tPa+~(R4X=o=T*QD3@W7>k8&=bVg zxggd}0Xgy=8w_qB2+mB&9fiVRJ;7-AL**Z+5nepM&r9F6qFHy#V7Y>`O2fxhet0(! zt0#eZd>^>VOTcxl7|f%)Kr9*wa&Q;$yOy(C=pRV#Xj9S4`EaoRHZ|0!+3@vNUz1VV z-z`JiB)L}ZXUqdSf|xf1%=~R&UMd2!qSQNG`0s^$Fb}Q+IV}cc-}XKrAphWks#AmUduMrxeQjwbh~x<%hrI3w0>L$xWoUa$-SHOmaz3o0MQSwqK%={fhHp6D zlAPsA&Tikq^OGlldFo(|D}GHAe-C{Gvm_lvQk?A{`0ob7;w;U@H3rcU|Dnu4jmD!p zy7r9V+A3+VtH{wS=}vo)iT%LL-2|>ng>^FgD#36*7tFn@K*sm>qeYT4^bgKT-7yo8 z7O8Bq8Vxnj`7{mfH@6KoTXJ^EYxp?P@Dp?}_pJig#R4!ZO6tw{{pPttAW|2C9M^+F zsXjosExF@_G#n#cI{PVxV3j4PQGd~$Ue50dgGEb&

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