CI95.CPI = function(data, likert = 3, boot = 10000) | | n.question = length(unique(data[,2])) | CI95 = matrix(0, n.question, 2) | Colnames(CI95) = c(“LL”, “UL”) | data = likertCheck(data, likert) | ### Boostrapping | ### Create the matrix for storing the CPIs of each simulation | B.CPI = matrix(0, boot, n.question) | For (i in 1:boot) | { | set.seed(i) | B.index = sample(1:nrow(data), nrow(data), replace = TRUE) | B.Data = data[B.index,]∣ | if (length(CPICal(data = B.Data)[,3]) == n.question) | B.CPI[i,] = CPICal(data = B.Data)[,3] | else B.CPI[i,] = NA | } | for (i in 1:n.question) | CI95[i,] = quantile(B.CPI[,i], c(.025, .975), na.rm = TRUE) | CI95 | |
|