code simplification, comment

R/kappa.R

@@ -105,6 +105,7 @@ kappa2 <- function (ratings, robust = FALSE, ratingScale = NULL) {
 #' Setting `variant='conger'` gives the variant of Conger (1980) that reduces to Cohen's kappa when m=2 raters. 
 #' It assumes identical raters for the different subjects (two-way ANOVA setting). The chance agreement is based on the category proportions of each rater separately.
 #' Typically, the Conger variant yields slightly higher values than Fleiss kappa.
+#' Variant robust assumes a chance agreement of two raters to be simply 1/q, where q is the number of categories (uniform model).
 #'
 #' @param ratings matrix (dimension nxr), containing the ratings as subjects by raters
 #' @param variant Which variant of kappa? Default is Fleiss (1971). Other options are Conger (1980) or robust variant.
@@ -155,9 +156,11 @@ kappam.fleiss <- function (ratings, variant = c("fleiss", "conger", "robust", "u
   sj_cnt_tab <- apply(ratings, 1,
                       FUN = function(ro) tabulate(factor(ro, levels = ratingScale), nbins = nCat))
   cat_cnt <- rowSums(sj_cnt_tab)
-  cat_ssq <- crossprod(cat_cnt)[1]
+  cat_ssq <- crossprod(cat_cnt)[1L]
+  
+  # sum((colSums(sj_cnt_tab^2) - nr) / (nr * (nr - 1) * nSj))
+  agreeP <- mean((colSums(sj_cnt_tab^2) - nr)) / (nr * (nr - 1))
   
-  agreeP <- sum((colSums(sj_cnt_tab^2) - nr) / (nr * (nr - 1) * nSj))
   switch(variant, 
          fleiss = {
            method <- "Fleiss' Kappa for m Raters"