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+#' Construct a string to report mean and SD
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+
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+#' @param v a vector of values
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+#'
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+#' @return a combined string
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+#'
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+#' @export
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+
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+get.mean<-function(v){
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+ base::sprintf('%.0f (%.0f)',base::mean(v,na.rm=TRUE),stats::sd(v,na.rm=TRUE))
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+}
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+
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+#' Construct a string to report median and range
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+#'
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+#' @param v a vector of values
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+#'
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+#' @return a combined string
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+#'
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+#' @export
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+
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+get.median<-function(v){
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+ base::sprintf('%.0f (%.0f-%.0f)',stats::median(v,na.rm=TRUE),base::min(v,na.rm=TRUE),base::max(v,na.rm=TRUE))
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+}
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+
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+#' Construct a string to report median and quartiles
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+#'
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+#' @param v a vector of values
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+#'
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+#' @return a combined string
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+#'
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+#' @export
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+
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+
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+get.medianQ<-function(v){
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+ q=base::c(0.25,0.75)
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+ qv=stats::quantile(v,probs=q,na.rm=TRUE)
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+ base::print(qv[1])
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+ base::sprintf('%.0f (%.0f-%.0f)',stats::median(v,na.rm=TRUE),qv[1],qv[2])
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+}
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+
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+#' Construct a string to report count and portion that match comma separated string list
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+#'
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+#' @param v a vector of values
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+#' @param val comma separated list of values
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+#'
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+#' @return a combined string
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+#'
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+#' @export
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+
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+get.portion<-function(v,val){
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+ vals<-base::as.integer(base::strsplit(base::as.character(val),',')[[1]])
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+ n1=base::length(v[base::is.element(v,vals)])
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+ base::sprintf('%.0f (%.0f %%)',n1,100*n1/base::length(v))
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+}
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+
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+#' Report count of elements in v that match comma separated string list
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+#'
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+#' @param v a vector of values
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+#' @param val comma separated list of values
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+#'
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+#' @return a combined string
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+#'
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+#' @export
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+
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+get.events<-function(v,val){
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+ vals<-base::as.integer(base::strsplit(base::as.character(val),',')[[1]])
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+ base::length(v[base::is.element(v,vals)])
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+}
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+
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+#' Repeat function and merge output in a vector
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+#'
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+#' @param func function to perform, with elements v and a key k
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+#' @param v parameter of the func
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+#' @param keys a set of k values for the func
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+#'
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+#' @return a combined output
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+#'
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+#' @export
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+
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+get.series<-function(func,v,keys=c()){
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+ out=base::c()
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+ for (k in keys){
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+ out=base::c(out,func(v,k))
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+ }
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+ out
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+}
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+
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+#' Construct a contingency table
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+#'
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+#' @param df data frame with entries selected by an outcome variable
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+#' @param df1 complementary data frame to df
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+#' @param var variable to test dependency for
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+#' @param keys possible values of var
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+#'
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+#' @return contingency table as a data frame, rows are keys, and columns are v for df and v1 for df1
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+#'
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+#' @export
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+
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+
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+get.contingency<-function(df,df1,var,keys){
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+ v<-base::c()
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+ v1<-base::c()
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+ #for (k in names(z)){
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+ #keys=z[[k]][,'Key']
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+ v<-base::c(v,get.series(get.events,df[,var],keys))
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+ v1<-base::c(v1,get.series(get.events,df1[,var],keys))
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+ if (base::length(keys)==1){
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+ v<-base::c(v,base::nrow(df)-v[1])
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+ v1<-base::c(v1,base::nrow(df1)-v1[1])
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+ }
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+ base::data.frame(v=v,v1=v1)
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+}
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+
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+#' Determine statistical significance of df/df1 splitting for variable using chi-square test
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+#'
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+#' @param df data frame with entries selected by an outcome variable
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+#' @param df1 complementary data frame to df
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+#' @param var variable to test dependency for
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+#' @param keys possible values of var
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+#'
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+#' @return chisq.test output
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+#'
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+#' @export
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+
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+get.chisq<-function(df,df1,var,keys){
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+ cf<-get.contingency(df,df1,var,keys)
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+ stats::chisq.test(cf,simulate.p.value=TRUE)$p.value
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+}
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+
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+#' Determine statistical significance of df/df1 splitting for variable using FIsher's exact test
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+#'
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+#' @param df data frame with entries selected by an outcome variable
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+#' @param df1 complementary data frame to df
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+#' @param var variable to test dependency for
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+#' @param keys possible values of var
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+#'
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+#' @return fisher.test output
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+#'
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+#' @export
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+
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+get.fisher<-function(df,df1,var,keys){
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+ cf<-get.contingency(df,df1,var,keys)
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+ stats::fisher.test(cf,simulate.p.value=TRUE)$p.value
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+}
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+
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+#' Determine statistical significance of df/df1 splitting for a continous variable (MWU/Wilcox)
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+#'
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+#' @param df data frame with entries selected by an outcome variable
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+#' @param df1 complementary data frame to df
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+#' @param var variable to test dependency for
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+#'
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+#' @return wilcox.test output
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+#'
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+#' @export
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+
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+get.u<-function(df,df1,var){
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+ stats::wilcox.test(df[,var],df1[,var])$p.value
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+}
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+
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+#' Determine statistical significance of df/df1 splitting for a continous variable (T-test)
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+#'
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+#' @param df data frame with entries selected by an outcome variable
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+#' @param df1 complementary data frame to df
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+#' @param var variable to test dependency for
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+#'
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+#' @return wilcox.test output
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+#'
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+#' @export
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+
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+get.t<-function(df,df1,var){
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+ stats::t.test(df[,var],df1[,var])$p.value
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+}
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+
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