mirror of
https://github.com/agdamsbo/daDoctoR.git
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166 lines
3.6 KiB
R
166 lines
3.6 KiB
R
#' A repeated regression function for change-in-estimate analysis
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#'
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#' For bivariate analyses.
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#' @param y Effect meassure.
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#' @param v1 Main variable in model
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#' @param string String of columnnames from dataframe to include. Use dput().
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#' @keywords change-in-estimate
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#' @export
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#' @examples
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#' cie_test()
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cie_test<-function(y,v1,string,data,logistic=FALSE,cut=0.1,v2=NULL,v3=NULL){
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## Calculating variables, that should be included for a change in estimate analysis.
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## v1-3 are possible locked variables, y is the outcome vector.
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## String defines variables to test, and is provided as vector of variable names. Use dput().
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## From "Modeling and variable selection in epidemiologic analysis." - S. Greenland, 1989.
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require(broom)
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d<-data
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x<-select(d,one_of(c(string)))
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if(logistic==FALSE){
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if (is.factor(y)){stop("Some kind of error message would be nice, but y should not be a factor!")}
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if (is.null(v2)&is.null(v3)){
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e<-as.numeric(round(coef(lm(y~v1)),3))[1]
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df<-data.frame(pred="base",b=e)
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for(i in 1:ncol(x)){
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m<-lm(y~v1+x[,i])
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b<-as.numeric(round(coef(m),3))[1]
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v<-x[,i]
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pred<-paste(names(x)[i])
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df<-rbind(df,cbind(pred,b))
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}
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t<-c(NA,ifelse(abs(e-as.numeric(df[-1,2]))>=(e*cut),"include","drop"))
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df<-cbind(df,t)
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}
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if (!is.null(v2)&is.null(v3)){
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e<-as.numeric(round(coef(lm(y~v1+v2)),3))[1]
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df<-data.frame(pred="base",b=e)
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for(i in 1:ncol(x)){
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m<-lm(y~v1+v2+x[,i])
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b<-as.numeric(round(coef(m),3))[1]
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v<-x[,i]
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pred<-paste(names(x)[i])
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df<-rbind(df,cbind(pred,b))
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}
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t<-c(NA,ifelse(abs(e-as.numeric(df[-1,2]))>=(e*cut),"include","drop"))
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df<-cbind(df,t)
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}
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if (!is.null(v2)&!is.null(v3)){
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e<-as.numeric(round(coef(lm(y~v1+v2+v3)),3))[1]
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df<-data.frame(pred="base",b=e)
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for(i in 1:ncol(x)){
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m<-lm(y~v1+v2+v3+x[,i])
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b<-as.numeric(round(coef(m),3))[1]
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v<-x[,i]
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pred<-paste(names(x)[i])
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df<-rbind(df,cbind(pred,b))
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}
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t<-c(NA,ifelse(abs(e-as.numeric(df[-1,2]))>=(e*cut),"include","drop"))
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df<-cbind(df,t)
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}}
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if(logistic==TRUE){
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if (!is.factor(y)){stop("Some kind of error message would be nice, but y should be a factor!")}
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if (is.null(v2)&is.null(v3)){
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e<-as.numeric(round(exp(coef(glm(y~v1,family=binomial()))),3))[1]
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df<-data.frame(pred="base",b=e)
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for(i in 1:ncol(x)){
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m<-glm(y~v1+x[,i],family=binomial())
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b<-as.numeric(round(exp(coef(m)),3))[1]
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v<-x[,i]
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pred<-paste(names(x)[i])
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df<-rbind(df,cbind(pred,b))
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}
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t<-c(NA,ifelse(abs(e-as.numeric(df[-1,2]))>=(e*cut),"include","drop"))
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df<-cbind(df,t)
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}
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if (!is.null(v2)&is.null(v3)){
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e<-as.numeric(round(exp(coef(glm(y~v1+v2,family=binomial()))),3))[1]
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df<-data.frame(pred="base",b=e)
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for(i in 1:ncol(x)){
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m<-glm(y~v1+v2+x[,i],family=binomial())
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b<-as.numeric(round(exp(coef(m)),3))[1]
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v<-x[,i]
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pred<-paste(names(x)[i])
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df<-rbind(df,cbind(pred,b))
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}
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t<-c(NA,ifelse(abs(e-as.numeric(df[-1,2]))>=(e*cut),"include","drop"))
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df<-cbind(df,t)
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}
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if (!is.null(v2)&!is.null(v3)){
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e<-as.numeric(round(exp(coef(glm(y~v1+v2+v3,family=binomial()))),3))[1]
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df<-data.frame(pred="base",b=e)
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for(i in 1:ncol(x)){
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m<-glm(y~v1+v2+v3+x[,i],family=binomial())
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b<-as.numeric(round(exp(coef(m)),3))[1]
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v<-x[,i]
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pred<-paste(names(x)[i])
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df<-rbind(df,cbind(pred,b))
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}
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t<-c(NA,ifelse(abs(e-as.numeric(df[-1,2]))>=(e*cut),"include","drop"))
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df<-cbind(df,t)
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}}
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result<-df
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return(df)
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}
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