Merge pull request #170 from pharmaverse/devel

CRAN feedback revisions #168

Author: alanaharris22

DESCRIPTION

@@ -6,7 +6,10 @@ Authors@R: c(
     person("Tim", "Barnett", email = "[email protected]", role = c("cph","aut", "cre")), 
     person("Nathan", "Rees", email = "[email protected]", role = c("aut")), 
     person("Alana", "Harris", email = "[email protected]", role = c("aut")))
-Description: Functions for applying a datacut to SDTM.
+Description: Supports the process of applying a cut to Standard Data Tabulation Model (SDTM),
+    as part of the analysis of specific points in time of the data, normally as part of 
+    investigation into clinical trials. The functions support different approaches of
+    cutting to the different domains of SDTM normally observed.
 License: Apache License (>= 2)
 Encoding: UTF-8
 Language: en-US

man/datacutr-package.Rd

@@ -114,6 +114,4 @@ cut_data <- purrr::map(
 
 # Add on data which is not cut
 final_data <- c(cut_data, no_cut_list, list(dcut = dcut))
-
-list2env(final_data, envir = globalenv())
 ```

vignettes/examplemodular.Rmd

@@ -78,9 +78,4 @@ cut_data <- process_cut(
   cut_var = DCUTDTM,
   special_dm = TRUE
 )
-
-
-# Save cut SDTMs to environment -------------------------------------------
-
-list2env(cut_data, envir = globalenv())
 ```

vignettes/examplewrapped.Rmd

@@ -188,6 +188,4 @@ cut_data <- purrr::map(
 Lastly, we create the final list of all the cut SDTM data, adding in the SDTM where no cut was needed.
 ```{r, message=FALSE, warning=FALSE}
 final_data <- c(cut_data, no_cut_list, list(dcut = dcut))
-
-list2env(final_data, envir = globalenv())
 ```

vignettes/modular.Rmd

@@ -27,7 +27,6 @@ this wrapped approach may not be suitable if you wish to enable any study or pro
 * [Create DCUT Dataset](#dcut)
 * [Pre-process Datasets](#preprocess)
 * [Process Data Cut](#processcut)
-* [Save Final Cut Datasets](#save)
 
 ## Read in Data {#readdata}
 
@@ -99,12 +98,3 @@ cut_data <- process_cut(
   special_dm = TRUE
 )
 ```
-
-
-## Save Final Cut Datasets {#save}
-
-If necessary, we can save all of the cut SDTM datasets to the R environment. 
-
-```{r, message=FALSE, warning=FALSE}
-list2env(cut_data, envir = globalenv())
-```