Chi Square Analysis using for loop in R

Question

I\'m trying to do chi square analysis for all combinations of variables in the data and my code is:

Data <- esoph[ , 1:3]
OldStatistic <- NA
for(i in 1         


        

Answer 1

I wrote my own function. It creates a matrix where all nominal variables are tested against each other. It can also save the results as excel file. It displays all the pvalues that are smaller than 5%.

funMassChi <- function (x,delFirst=0,xlsxpath=FALSE) {
  options(scipen = 999)

  start <- (delFirst+1)
  ds <- x[,start:ncol(x)]

  cATeND <- ncol(ds)
  catID  <- 1:cATeND

  resMat <- ds[1:cATeND,1:(cATeND-1)]
  resMat[,] <- NA

    for(nCc in 1:(length(catID)-1)){
      for(nDc in (nCc+1):length(catID)){
        tryCatch({
          chiRes <- chisq.test(ds[,catID[nCc]],ds[,catID[nDc]])
          resMat[nDc,nCc]<- chiRes[[3]]
        }, error=function(e){cat(paste("ERROR :","at",nCc,nDc, sep=" "),conditionMessage(e), "\n")})
      }
    }
  resMat[resMat > 0.05] <- "" 
  Ergebnis <- cbind(CatNames=names(ds),resMat)
  Ergebnis <<- Ergebnis[-1,] 

  if (!(xlsxpath==FALSE)) {
     write.xlsx(x = Ergebnis, file = paste(xlsxpath,"ALLChi-",Sys.Date(),".xlsx",sep=""),
             sheetName = "Tabelle1", row.names = FALSE)
  }
}

funMassChi(categorialDATA,delFirst=3,xlsxpath="C:/folder1/folder2/")

delFirst can delete the first n columns. So if you have an count index or something you dont want to test.

I hope this can help anyone else.

Answer 2

A sample of your data would be appreciated, but I think this will work for you. First, create a combination of all columns with combn. Then write a function to use with an apply function to iterate through the combos. I like to use plyr since it is easy to specify what you want for a data structure on the back end. Also note you only need to compute the chi square test once for each combination of columns, which should speed things up quite a bit as well.

library(plyr)

combos <- combn(ncol(Dat),2)

adply(combos, 2, function(x) {
  test <- chisq.test(Dat[, x[1]], Dat[, x[2]])

  out <- data.frame("Row" = colnames(Dat)[x[1]]
                    , "Column" = colnames(Dat[x[2]])
                    , "Chi.Square" = round(test$statistic,3)
                    ,  "df"= test$parameter
                    ,  "p.value" = round(test$p.value, 3)
                    )
  return(out)

})