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#' multi_transmat: transition matrix of all the items
#'
#' @title Creates a transition matrix for each item.
#' @description Needs an 'interleaved' dataframe (see interleave function). Pre-test item should be followed by corresponding post-item item etc.
#' Don't knows must be coded as NA. Function handles items without don't know responses.
#' The function is used internally. It calls transmat.
#' @param pre_test Required. data.frame carrying responses to pre-test questions.
#' @param pst_test Required. data.frame carrying responses to post-test questions.
#' @param subgroup a Boolean vector identifying the subset. Default is NULL.
#' @param force9 Optional. There are cases where DK data doesn't have DK. But we need the entire matrix. By default it is FALSE.
#' @return matrix with rows = total number of items + 1 (last row contains aggregate distribution across items)
#' number of columns = 4 when no don't know, and 9 when there is a don't know option
#' @export
#' @examples
#' pre_test <- data.frame(pre_item1=c(1,0,0,1,0), pre_item2=c(1,NA,0,1,0))
#' pst_test <- data.frame(pst_item1=pre_test[,1] + c(0,1,1,0,0),
#' pst_item2 = pre_test[,2] + c(0,1,0,0,1))
#' multi_transmat(pre_test, pst_test)
multi_transmat <- function (pre_test = NULL, pst_test=NULL, subgroup=NULL, force9=FALSE)
{
# Checks
if (!is.data.frame(pre_test)) stop("Specify pre_test data.frame.") # pre_test data frame is missing
if (!is.data.frame(pst_test)) stop("Specify pst_test data.frame.") # post_test data frame is missing
if(length(pre_test)!=length(pst_test)) stop("Lengths of pre_test and pst_test must be the same.") # If different no. of items
# Subset
if (!is.null(subgroup))
{
pre_test <- subset(pre_test, subgroup)
pst_test <- subset(pst_test, subgroup)
}
# No. of items
n_items <- length(pre_test)
# Initialize results
res <- list()
# Get transition matrix for each item pair
for (i in 1:n_items)
{
# cat("\n Item", i, "\n")
res[[i]] <- transmat(pre_test[,i], pst_test[,i], force9=force9)
}
# Prepping results
row_names <- paste0("item", 1:n_items)
col_names <- names(res[[1]])
res <- matrix(unlist(res), nrow=n_items, byrow=T, dimnames=list(row_names, col_names))
res <- rbind(res, colSums(res, na.rm=T))
rownames(res)[nrow(res)] <- "agg"
#cat("\n Aggregate \n")
#prmatrix(res)
#cat("\n")
return(invisible(res))
}
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