new function 'print_pred_stratum'. see description

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: daDoctoR
 Title: Functions For Health Research
-Version: 0.21.8
+Version: 0.21.9
 Year: 2021
 Author: Andreas Gammelgaard Damsbo <agdamsbo@pm.me>
 Maintainer: Andreas Gammelgaard Damsbo <agdamsbo@pm.me>

NAMESPACE

@@ -23,6 +23,7 @@ export(print_diff_byvar)
 export(print_log)
 export(print_olr)
 export(print_pred)
+export(print_pred_stratum)
 export(print_reg_diff_bin)
 export(quantile_cut)
 export(redcap_clean_csv)

R/print_pred.R

@@ -21,6 +21,7 @@ print_pred<-function(meas,adj,data,dec=2,n.by.adj=FALSE,p.val=FALSE){
   ## - Include ANOVA in output list, flag to include
 
   require(dplyr)
+  require(broom)
 
   d<-data
   m<-d[,c(meas)]

R/print_pred_stratum.R

@@ -0,0 +1,38 @@
+#' Extension to the print_pred function, for by stratum analysis.
+#'
+#' Outputs list of results from 'print_pred' for the whole data set and for each stratum defined by 'strat'.
+#' Suitable to assist in determining whether a variable is a confounder or effect modifier.
+#' Ref: https://open.oregonstate.education/epidemiology/chapter/effect-modification/
+#' @param meas binary outcome measure variable, column name in data.frame as a string. Can be numeric or factor. Result is calculated accordingly.
+#' @param adj variables to adjust for, as string.
+#' @param strat stratum to stratify, variable name as string
+#' @param data dataframe of data.
+#' @param include.stratum flag to set if stratum variable should be included in first analysis of non-stratified data.
+#' @keywords stratum
+#' @export
+#' @examples
+#'   data('mtcars')
+#'   mtcars$vs<-factor(mtcars$vs)
+#'   mtcars$am<-factor(mtcars$am)
+#'   print_pred_stratum(meas="mpg",strat="vs",adj=c("disp","wt","am"),data=mtcars,include.stratum=TRUE)
+
+print_pred_stratum<-function(meas,adj,strat,data,dec,include.stratum=TRUE){
+  require(daDoctoR)
+  require(dplyr)
+
+  if (include.stratum==TRUE){
+    ls<-list(all=print_pred(meas = meas,adj=c(strat,adj),data=data))
+  }
+  if (include.stratum==FALSE) {
+    ls<-list(all=print_pred(meas = meas,adj=adj,data=data))
+  }
+
+  strt<-data[, c(strat)]
+  for (i in 1:length(levels(factor(strt)))){
+    d_str<-data[data[[strat]]==levels(data[[strat]])[i], c(meas,adj)]
+    ls_str<-list(print_pred(meas = meas,adj=adj,data=d_str))
+    names(ls_str)<-levels(factor(strt))[i]
+    ls<-append(ls,ls_str)
+  }
+  return(ls)
+}

README.md

@@ -16,3 +16,6 @@ I'm currently working on improving the code to be more universal
 - Include sample data to use with special functions
 - Include coding examples with all functions
 
+## New functions
+- Test for confounders and/or effect modifiers
+- Test for collinearity

man/print_pred_stratum.Rd

@@ -0,0 +1,31 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/print_pred_stratum.R
+\name{print_pred_stratum}
+\alias{print_pred_stratum}
+\title{Extension to the print_pred function, for by stratum analysis.}
+\usage{
+print_pred_stratum(meas, adj, strat, data, dec, include.stratum = TRUE)
+}
+\arguments{
+\item{meas}{binary outcome measure variable, column name in data.frame as a string. Can be numeric or factor. Result is calculated accordingly.}
+
+\item{adj}{variables to adjust for, as string.}
+
+\item{strat}{stratum to stratify, variable name as string}
+
+\item{data}{dataframe of data.}
+
+\item{include.stratum}{flag to set if stratum variable should be included in first analysis of non-stratified data.}
+}
+\description{
+Outputs list of results from 'print_pred' for the whole data set and for each stratum defined by 'strat'.
+Suitable to assist in determining whether a variable is a confounder or effect modifier.
+Ref: https://open.oregonstate.education/epidemiology/chapter/effect-modification/
+}
+\examples{
+  data('mtcars')
+  mtcars$vs<-factor(mtcars$vs)
+  mtcars$am<-factor(mtcars$am)
+  print_pred_stratum(meas="mpg",strat="vs",adj=c("disp","wt","am"),data=mtcars,include.stratum=TRUE)
+}
+\keyword{stratum}

update local version.R

@@ -19,3 +19,5 @@ library(daDoctoR)
 # install.packages("daDoctoR.tar.gz", repos = NULL, type = "source")
 
 # library(daDoctoR)
+
+