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datashield · Jan 1, 2015 · a8723e8 · a8723e8
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: dsStatsClient
 Maintainer: <[email protected]>
 Author: <[email protected]>
-Version: 3.0.1
+Version: 4.0.0
 License: GPL-3
 Title: DataSHIELD client site stattistical functions
 Description: DataSHIELD client site stattistical functions

diff --git a/R/ds.cor.R b/R/ds.cor.R
@@ -1,5 +1,5 @@
 #' 
-#' @title Computes the correlation between two or more vectors
+#' @title Computes correlation between two or more vectors
 #' @description This is similar to the R base function 'cor'.
 #' @details In addition to computing correlations this function, unlike
 #' the R base function 'cor', produces a table outlining the number of complete cases 
@@ -19,54 +19,39 @@
 #' @export
 #' @examples {
 #' 
-#' # load that contains the login details
-#' data(logindata)
+#'   # load that contains the login details
+#'   data(logindata)
 #' 
-#' # login and assign specific variable(s)
-#' # (by default the assigned dataset is a dataframe named 'D')
-#' myvar <- list('LAB_HDL', 'LAB_TSC', 'GENDER')
-#' opals <- datashield.login(logins=logindata,assign=TRUE,variables=myvar)
+#'   # login and assign specific variable(s)
+#'   # (by default the assigned dataset is a dataframe named 'D')
+#'   myvar <- list('LAB_HDL', 'LAB_TSC', 'GENDER')
+#'   opals <- datashield.login(logins=logindata,assign=TRUE,variables=myvar)
 #' 
-#' # Example 1: generate the correlation matrix for the assigned dataset 'D' 
-#' # which contains 4 vectors (2 continuous and 1 categorical)
-#' ds.cor(x='D')
+#'   # Example 1: generate the correlation matrix for the assigned dataset 'D' 
+#'   # which contains 4 vectors (2 continuous and 1 categorical)
+#'   ds.cor(x='D')
 #' 
-#' # Example 2: calculate the correlation between two vectors (first assign some vectors from the dataframe 'D')
-#' ds.assign(newobj='labhdl', toAssign='D$LAB_HDL')
-#' ds.assign(newobj='labtsc', toAssign='D$LAB_TSC')
-#' ds.assign(newobj='gender', toAssign='D$GENDER')
-#' ds.cor(x='labhdl', y='labtsc')
-#' ds.cor(x='labhdl', y='gender')
+#'   # Example 2: calculate the correlation between two vectors (first assign some vectors from the dataframe 'D')
+#'   ds.assign(newobj='labhdl', toAssign='D$LAB_HDL')
+#'   ds.assign(newobj='labtsc', toAssign='D$LAB_TSC')
+#'   ds.assign(newobj='gender', toAssign='D$GENDER')
+#'   ds.cor(x='labhdl', y='labtsc')
+#'   ds.cor(x='labhdl', y='gender')
 #' 
-#' # clear the Datashield R sessions and logout
-#' datashield.logout(opals)
+#'   # clear the Datashield R sessions and logout
+#'   datashield.logout(opals)
 #' 
 #' }
 #' 
-ds.cor = function(x=NULL, y=NULL, naAction='pairwise.complete.obs', datasources=NULL)
-{
+ds.cor = function(x=NULL, y=NULL, naAction='pairwise.complete.obs', datasources=NULL){
 
-  # if no opal login details were provided look for 'opal' objects in the environment
+  # if no opal login details are provided look for 'opal' objects in the environment
   if(is.null(datasources)){
-    findLogin <- getOpals()
-    if(findLogin$flag == 1){
-      datasources <- findLogin$opals
-    }else{
-      if(findLogin$flag == 0){
-        stop(" Are yout logged in to any server? Please provide a valid opal login object! ", call.=FALSE)
-      }else{
-        message(paste0("More than one list of opal login object were found: '", paste(findLogin$opals,collapse="', '"), "'!"))
-        userInput <- readline("Please enter the name of the login object you want to use: ")
-        datasources <- eval(parse(text=userInput))
-        if(class(datasources[[1]]) != 'opal'){
-          stop("End of process: you failed to enter a valid login object", call.=FALSE)
-        }
-      }
-    }
+    datasources <- findLoginObjects()
   }
 
   if(is.null(x)){
-    stop("x=NULL. Please provide the names of two numeric vectors!", call.=FALSE)
+    stop("x must be the name of a numeric vector or a table structure (matrix or data frame)", call.=FALSE)
   }else{
     defined <- isDefined(datasources, x)
   }
@@ -76,9 +61,7 @@ ds.cor = function(x=NULL, y=NULL, naAction='pairwise.complete.obs', datasources=
 
   if(typ=='numeric' | typ=='integer' | typ=='factor'){
     if(is.null(y)){
-      message(" ALERT!")
-      message(" y is set to NULL whilst x is a numeric vector, please provide a second vector")
-      stop(" End of process!", call.=FALSE)
+      stop("If x is a numeric vector, y must be a numeric vector!", call.=FALSE)
     }else{
       defined2 <- isDefined(datasources, y)
       typ2 <- checkClass(datasources, y)
@@ -87,7 +70,7 @@ ds.cor = function(x=NULL, y=NULL, naAction='pairwise.complete.obs', datasources=
 
   if(typ=='matrix' | typ=='data.frame' & !(is.null(y))){
     y <- NULL
-    warning(" x is a matrix or a dataframe; y will be ignored and a correlation matrix computed for x!")
+    warning("x is a matrix or a data frame; y will be ignored and a correlation matrix computed for x!")
   }
 
   # name of the studies to be used in the output

diff --git a/R/ds.corTest.R b/R/ds.corTest.R
@@ -11,48 +11,34 @@
 #' @export
 #' @examples {
 #' 
-#' # load that contains the login details
-#' data(logindata)
+#'   # load that contains the login details
+#'   data(logindata)
 #' 
-#' # login and assign specific variable(s)
-#' # (by default the assigned dataset is a dataframe named 'D')
-#' myvar <- list('LAB_TSC', 'LAB_HDL')
-#' opals <- datashield.login(logins=logindata,assign=TRUE,variables=myvar)
+#'   # login and assign specific variable(s)
+#'   # (by default the assigned dataset is a dataframe named 'D')
+#'   myvar <- list('LAB_TSC', 'LAB_HDL')
+#'   opals <- datashield.login(logins=logindata,assign=TRUE,variables=myvar)
 #' 
-#' # test for correlation between the variables 'LAB_TSC' and 'LAB_HDL'
-#' ds.corTest(x='D$LAB_TSC', y='D$LAB_HDL')
+#'   # test for correlation between the variables 'LAB_TSC' and 'LAB_HDL'
+#'   ds.corTest(x='D$LAB_TSC', y='D$LAB_HDL')
 #' 
-#' # clear the Datashield R sessions and logout
-#' datashield.logout(opals)
+#'   # clear the Datashield R sessions and logout
+#'   datashield.logout(opals)
 #' 
 #' }
 #' 
 ds.corTest = function(x=NULL, y=NULL, datasources=NULL){
 
-  # if no opal login details were provided look for 'opal' objects in the environment
+  # if no opal login details are provided look for 'opal' objects in the environment
   if(is.null(datasources)){
-    findLogin <- getOpals()
-    if(findLogin$flag == 1){
-      datasources <- findLogin$opals
-    }else{
-      if(findLogin$flag == 0){
-        stop(" Are yout logged in to any server? Please provide a valid opal login object! ", call.=FALSE)
-      }else{
-        message(paste0("More than one list of opal login object were found: '", paste(findLogin$opals,collapse="', '"), "'!"))
-        userInput <- readline("Please enter the name of the login object you want to use: ")
-        datasources <- eval(parse(text=userInput))
-        if(class(datasources[[1]]) != 'opal'){
-          stop("End of process: you failed to enter a valid login object", call.=FALSE)
-        }
-      }
-    }
+    datasources <- findLoginObjects()
   }
 
   if(is.null(x)){
-    stop("x=NULL. Please provide the names of two numeric vectors!", call.=FALSE)
+    stop("x=NULL. Please provide the names of the 1st vector!", call.=FALSE)
   }
   if(is.null(y)){
-    stop("y=NULL. Please provide the names of two numeric vectors!", call.=FALSE)
+    stop("y=NULL. Please provide the names of the 2nd numeric vector!", call.=FALSE)
   }
 
   # the input variable might be given as column table (i.e. D$object)

diff --git a/R/ds.cov.R b/R/ds.cov.R
@@ -19,50 +19,36 @@
 #' @export
 #' @examples {
 #' 
-#' # load that contains the login details
-#' data(logindata)
+#'   # load that contains the login details
+#'   data(logindata)
 #' 
-#' # login and assign specific variable(s)
-#' # (by default the assigned dataset is a dataframe named 'D')
-#' myvar <- list('LAB_HDL', 'LAB_TSC', 'GENDER')
-#' opals <- datashield.login(logins=logindata,assign=TRUE,variables=myvar)
+#'   # login and assign specific variable(s)
+#'   # (by default the assigned dataset is a dataframe named 'D')
+#'   myvar <- list('LAB_HDL', 'LAB_TSC', 'GENDER')
+#'   opals <- datashield.login(logins=logindata,assign=TRUE,variables=myvar)
 #' 
-#' # Example 1: generate the covariance matrix for the assigned dataset 'D' 
-#' # which contains 4 vectors (2 continuous and 1 categorical)
-#' ds.cov(x='D')
+#'   # Example 1: generate the covariance matrix for the assigned dataset 'D' 
+#'   # which contains 4 vectors (2 continuous and 1 categorical)
+#'   ds.cov(x='D')
 #' 
-#' # Example 2: calculate the covariance between two vectors 
-#' # (first assign the vectors from 'D')
-#' ds.assign(newobj='labhdl', toAssign='D$LAB_HDL')
-#' ds.assign(newobj='labtsc', toAssign='D$LAB_TSC')
-#' ds.assign(newobj='gender', toAssign='D$GENDER')
-#' ds.cov(x='labhdl', y='labtsc')
-#' ds.cov(x='labhdl', y='gender')
+#'   # Example 2: calculate the covariance between two vectors 
+#'   # (first assign the vectors from 'D')
+#'   ds.assign(newobj='labhdl', toAssign='D$LAB_HDL')
+#'   ds.assign(newobj='labtsc', toAssign='D$LAB_TSC')
+#'   ds.assign(newobj='gender', toAssign='D$GENDER')
+#'   ds.cov(x='labhdl', y='labtsc')
+#'   ds.cov(x='labhdl', y='gender')
 #' 
-#' # clear the Datashield R sessions and logout
-#' datashield.logout(opals)
+#'   # clear the Datashield R sessions and logout
+#'   datashield.logout(opals)
 #' 
 #' }
 #' 
 ds.cov = function(x=NULL, y=NULL, naAction='pairwise.complete.obs', datasources=NULL){
 
-  # if no opal login details were provided look for 'opal' objects in the environment
+  # if no opal login details are provided look for 'opal' objects in the environment
   if(is.null(datasources)){
-    findLogin <- getOpals()
-    if(findLogin$flag == 1){
-      datasources <- findLogin$opals
-    }else{
-      if(findLogin$flag == 0){
-        stop(" Are yout logged in to any server? Please provide a valid opal login object! ", call.=FALSE)
-      }else{
-        message(paste0("More than one list of opal login object were found: '", paste(findLogin$opals,collapse="', '"), "'!"))
-        userInput <- readline("Please enter the name of the login object you want to use: ")
-        datasources <- eval(parse(text=userInput))
-        if(class(datasources[[1]]) != 'opal'){
-          stop("End of process: you failed to enter a valid login object", call.=FALSE)
-        }
-      }
-    }
+    datasources <- findLoginObjects()
   }
 
   if(is.null(x)){
@@ -76,9 +62,7 @@ ds.cov = function(x=NULL, y=NULL, naAction='pairwise.complete.obs', datasources=
 
   if(typ=='numeric' | typ=='integer' | typ=='factor'){
     if(is.null(y)){
-      message(" ALERT!")
-      message(" y is set to NULL whilst x is a numeric vector, please provide a second vector")
-      stop(" End of process!", call.=FALSE)
+      stop("If x is a numeric vector, y must be a numeric vector!", call.=FALSE)
     }else{
       defined2 <- isDefined(datasources, y)
       typ2 <- checkClass(datasources, y)
@@ -87,7 +71,7 @@ ds.cov = function(x=NULL, y=NULL, naAction='pairwise.complete.obs', datasources=
 
   if(typ=='matrix' | typ=='data.frame' & !(is.null(y))){
     y <- NULL
-    warning(" x is a matrix or a dataframe; y will be ignored and a covariance matrix computed for x!")
+    warning("x is a matrix or a dataframe; y will be ignored and a covariance matrix computed for x!")
   }
 
   # name of the studies to be used in the output

diff --git a/R/ds.tTest.R b/R/ds.tTest.R
@@ -21,80 +21,67 @@
 #' @param datasources a list of opal object(s) obtained after login in to opal servers;
 #' these objects hold also the data assign to R, as \code{dataframe}, from opal datasources.
 #' @return a list containing the following elements:
-#' \code{statistic} the value of the t-statistic 
-#' \code{parameter} the degrees of freedom for the t-statistic 
-#' \code{p.value} p.value the p-value for the test 
-#' \code{conf.int} a confidence interval for the mean appropriate to the specified alternative hypothesis 
-#' \code{estimate} the estimated mean or difference in means depending on whether it was a one-sample test or a two-sample test 
-#' \code{null.value} the specified hypothesized value of the mean or mean difference depending on whether it was a one-sample test or a two-sample test 
+#' \code{statistic} the value of the t-statistic. 
+#' \code{parameter} the degrees of freedom for the t-statistic. 
+#' \code{p.value} p.value the p-value for the test. 
+#' \code{conf.int} a confidence interval for the mean appropriate to the specified alternative hypothesis. 
+#' \code{estimate} the estimated mean or difference in means depending on whether it was a one-sample test 
+#' or a two-sample test. 
+#' \code{null.value} the specified hypothesized value of the mean or mean difference depending on whether it 
+#' was a one-sample test or a two-sample test.
 #' \code{alternative} a character string describing the alternative hypothesis 
 #' \code{method} a character string indicating what type of t-test was performed 
 #' @author Isaeva, J.; Gaye, A.
 #' @export
-#' @examples
-#' {
+#' @examples {
 #' 
-#' # load that contains the login details
-#' data(logindata)
+#'   # load that contains the login details
+#'   data(logindata)
 #' 
-#' # login and assign specific variable(s)
-#' myvar <- list("LAB_HDL", "LAB_TSC")
-#' opals <- datashield.login(logins=logindata,assign=TRUE,variables=myvar)
+#'   # login and assign specific variable(s)
+#'   myvar <- list("LAB_HDL", "LAB_TSC")
+#'   opals <- datashield.login(logins=logindata,assign=TRUE,variables=myvar)
 #' 
-#' # Example 1: Run a t.test of the pooled data for the variables 'LAB_HDL' and 'LAB_TSC' - default
-#' ds.tTest(x='D$LAB_HDL', y='D$LAB_TSC')
+#'   # Example 1: Run a t.test of the pooled data for the variables 'LAB_HDL' and 'LAB_TSC' - default
+#'   ds.tTest(x='D$LAB_HDL', y='D$LAB_TSC')
 #' 
-#' # Example 2: Run a t.test for each study separately for the same variables as above
-#' ds.tTest(x='D$LAB_HDL', y='D$LAB_TSC', type='split')
+#'   # Example 2: Run a t.test for each study separately for the same variables as above
+#'   ds.tTest(x='D$LAB_HDL', y='D$LAB_TSC', type='split')
 #' 
-#' # Example 3: Run a paired t.test of the pooled data
-#' ds.tTest(x='D$LAB_HDL', y='D$LAB_TSC', paired=TRUE)
+#'   # Example 3: Run a paired t.test of the pooled data
+#'   ds.tTest(x='D$LAB_HDL', y='D$LAB_TSC', paired=TRUE)
 #' 
-#' # Example 4: Run a paired t.test for each study separately
-#' ds.tTest(x='D$LAB_HDL', y='D$LAB_TSC', paired=TRUE, type='split')
+#'   # Example 4: Run a paired t.test for each study separately
+#'   ds.tTest(x='D$LAB_HDL', y='D$LAB_TSC', paired=TRUE, type='split')
 #' 
-#' # Example 5: Run a t.test of the pooled data with different alternatives
-#' ds.tTest(x='D$LAB_HDL', y='D$LAB_TSC', alternative='greater')
-#' ds.tTest(x='D$LAB_HDL', y='D$LAB_TSC', alternative='less')
+#'   # Example 5: Run a t.test of the pooled data with different alternatives
+#'   ds.tTest(x='D$LAB_HDL', y='D$LAB_TSC', alternative='greater')
+#'   ds.tTest(x='D$LAB_HDL', y='D$LAB_TSC', alternative='less')
 #' 
-#' # Example 6: Run a t.test of the pooled data with mu different from zero
-#' ds.tTest(x='D$LAB_HDL', y='D$LAB_TSC', mu=-4)
+#'   # Example 6: Run a t.test of the pooled data with mu different from zero
+#'   ds.tTest(x='D$LAB_HDL', y='D$LAB_TSC', mu=-4)
 #' 
-#' # Example 7: Run a t.test of the pooled data assuming that variances of variables are equal
-#' ds.tTest(x='D$LAB_HDL', y='D$LAB_TSC', var.equal=TRUE)
+#'   # Example 7: Run a t.test of the pooled data assuming that variances of variables are equal
+#'   ds.tTest(x='D$LAB_HDL', y='D$LAB_TSC', var.equal=TRUE)
 #' 
-#' # Example 8: Run a t.test of the pooled data with 90% confidence interval
-#' ds.tTest(x='D$LAB_HDL', y='D$LAB_TSC', conf.level=0.90)
+#'   # Example 8: Run a t.test of the pooled data with 90% confidence interval
+#'   ds.tTest(x='D$LAB_HDL', y='D$LAB_TSC', conf.level=0.90)
 #' 
-#' # Example 9: Run a one-sample t.test of the pooled data
-#' ds.tTest(x='D$LAB_HDL')
-#' # the below example should not work, paired t.test is not possible if the 'y' variable is missing
-#' # ds.tTest(x='D$LAB_HDL', paired=TRUE) 
+#'   # Example 9: Run a one-sample t.test of the pooled data
+#'   ds.tTest(x='D$LAB_HDL')
+#'   # the below example should not work, paired t.test is not possible if the 'y' variable is missing
+#'   # ds.tTest(x='D$LAB_HDL', paired=TRUE) 
 #' 
-#' # clear the Datashield R sessions and logout
-#' datashield.logout(opals)
+#'   # clear the Datashield R sessions and logout
+#'   datashield.logout(opals)
 #' 
 #'}
 #'
 ds.tTest <- function (x=NULL, y=NULL, type="combine", alternative="two.sided", mu=0, paired=FALSE, var.equal=FALSE, conf.level=0.95, datasources=NULL) {
 
-  # if no opal login details were provided look for 'opal' objects in the environment
+  # if no opal login details are provided look for 'opal' objects in the environment
   if(is.null(datasources)){
-    findLogin <- getOpals()
-    if(findLogin$flag == 1){
-      datasources <- findLogin$opals
-    }else{
-      if(findLogin$flag == 0){
-        stop(" Are yout logged in to any server? Please provide a valid opal login object! ", call.=FALSE)
-      }else{
-        message(paste0("More than one list of opal login object were found: '", paste(findLogin$opals,collapse="', '"), "'!"))
-        userInput <- readline("Please enter the name of the login object you want to use: ")
-        datasources <- eval(parse(text=userInput))
-        if(class(datasources[[1]]) != 'opal'){
-          stop("End of process: you failed to enter a valid login object", call.=FALSE)
-        }
-      }
-    }
+    datasources <- findLoginObjects()
   }
 
   if(is.null(x)){
@@ -187,9 +174,8 @@ ds.tTest <- function (x=NULL, y=NULL, type="combine", alternative="two.sided", m
       cally = paste0("subsetDS('",  x, "', not.na.x)")
       datashield.assign(datasources, 'xok', as.symbol(cally))
       cally = paste0("as.null(",  x, ")")
-      datashield.assign(datasources, 'yok', as.symbol(cally)) # does not matter that as.null(x) since we just want to make y to be NULL
-    }
-
+      datashield.assign(datasources, 'yok', as.symbol(cally)) # does not matter that as.null(x) since we just want to set y to NULL
+    }    
 
     if (paired) {
       cally = paste0("(yok)","*(",-1,")")