R/DescriptiveStrategy_m2.R

In derecost/LOGAN: Log File Analysis in International Large-Scale Assessments

#' Report: Descriptive statistics by strategy
#'
#' This is a function that reports a descriptive analysis of the strategy and
#' students performance
#'
#' @param data A \code{matrix} or \code{data.frame} where the 'strategy.var' and
#'   performance variables are
#' @param strategy.var A character string with the name of the strategy variable
#' @param performance.item A character string with the name of the item
#'   performance variable
#' @param performance.test A character string with the name of the test
#'   performance variable
#' @param PartialCredit Logical. It can be used when the item is partial credit
#'   score.
#'
#' @return This function returns a report with a descriptive analysis of the
#'   strategy and students performance
#'
#' @examples
#' m2$DescriptiveStrategy(cp025q01.treated, "votat", "CP025Q01", "PV1CPRO")
#'
DescriptiveStrategy <- function(data, strategy.var, performance.item,
                                performance.test, PartialCredit = FALSE) {
    if (PartialCredit == TRUE) {
        # Frequency table (N): categorical variables with partialCredit: only
        # accepts options: 0, 0.5 and 1
        tab.freqitem <- as.data.frame(table(data[, performance.item]))
        for (i in seq(length(tab.freqitem$Var1))) {
            if (i == 1 & tab.freqitem$Var1[i] != 0.5) {
                scalename2 <- tab.freqitem$Var1[i]
                n2 <- tab.freqitem$Freq[i]
                total2 <- tab.freqitem$Freq[i]
                perc2 <- sprintf("%.0f%%", 100 * n2/sum(tab.freqitem$Freq))
            } else if (tab.freqitem$Var1[i] == 0.5) {
                i = i + 1
                scalename2 <- paste0(scalename2, "|", tab.freqitem$Var1[i])
                n2 <- paste0(n2, "|", tab.freqitem$Freq[i - 1] + tab.freqitem$Freq[i])
                total2 <- total2 + tab.freqitem$Freq[i - 1] + tab.freqitem$Freq[i]
                perc2 <- paste0(perc2, "|",
                                sprintf("%.0f%%", 100 *
                                            (tab.freqitem$Freq[i - 1] * 0.5 +
                                                 tab.freqitem$Freq[i]) /
                                            sum(tab.freqitem$Freq)))
            }
        }
    } else {
        tab.freqitem <- as.data.frame(table(data[, performance.item]))
        for (i in seq(length(tab.freqitem$Var1))) {
            if (i == 1) {
                scalename2 <- tab.freqitem$Var1[i]
                n2 <- tab.freqitem$Freq[i]
                total2 <- tab.freqitem$Freq[i]
                perc2 <- sprintf("%.0f%%", 100 * n2 / sum(tab.freqitem$Freq))
            } else{
                scalename2 <- paste0(scalename2, "|", tab.freqitem$Var1[i])
                n2 <- paste0(n2, "|", tab.freqitem$Freq[i])
                total2 <- total2 + tab.freqitem$Freq[i]
                perc2 <- paste0(perc2, "|",
                                sprintf("%.0f%%", 100 * tab.freqitem$Freq[i] /
                                            sum(tab.freqitem$Freq)))
            }
        }
    }
    # Frequency table (N): categorical variables
    tab.freqvotat <- as.data.frame(table(data[, strategy.var]))
    for (i in seq(length(tab.freqvotat$Var1))) {
        if (i == 1) {
            scalename1 <- tab.freqvotat$Var1[i]
            n1 <- tab.freqvotat$Freq[i]
            total1 <- tab.freqvotat$Freq[i]
            perc1 <- sprintf("%.0f%%", 100 * tab.freqvotat$Freq[i] / sum(tab.freqvotat$Freq))
        } else{
            scalename1 <- paste0(scalename1, "|", tab.freqvotat$Var1[i])
            n1 <- paste0(n1, "|", tab.freqvotat$Freq[i])
            total1 <- total1 + tab.freqvotat$Freq[i]
            perc1 <- paste0(perc1, "|",
                            sprintf("%.0f%%", 100 * tab.freqvotat$Freq[i] /
                                        sum(tab.freqvotat$Freq)))
        }
    }

    tab.print <-
        as.data.frame(rbind(
            cbind(paste0("Strategy: ", strategy.var), scalename1, perc1, n1, total1),
            cbind(paste0("Performance: ", performance.item), scalename2, perc2, n2, total2)
        ))

    colnames(tab.print) <- c("Construct", "Scale","Relat. Freq.", "Frequencies", "Total N")
    message("\n Frequency table - Individual level")
    pander::pandoc.table(tab.print,split.tables = 100)

    #Chi-squared test of independence
    crostab.freqvotat <- table(data[, c(strategy.var, performance.item)])
    xtest.crostab <- stats::chisq.test(crostab.freqvotat)

    message("Measures of association between ", strategy.var, " and ",
        performance.item, " - Individual level")
    crostab.freqvotat <- rbind(crostab.freqvotat, apply(crostab.freqvotat, 2, sum))
    crostab.freqvotat <- cbind(crostab.freqvotat, apply(crostab.freqvotat, 1, sum))
    crostab.freqvotat <- cbind(row.names(crostab.freqvotat),
                               as.data.frame.matrix(crostab.freqvotat,
                                                    row.names = seq(dim(crostab.freqvotat)[1])))
    crostab.freqvotat[, 1] <- as.character(crostab.freqvotat[, 1])
    crostab.freqvotat[dim(crostab.freqvotat)[1], 1] <- "Total"
    names(crostab.freqvotat)[1] <- paste0(strategy.var, " / ", performance.item)
    names(crostab.freqvotat)[length(names(crostab.freqvotat))] <- "Total"

    value.p <- ifelse(round(xtest.crostab$p.value,4) < 0.01, "0.01",
                      round(xtest.crostab$p.value,4))
    pander::pandoc.table(crostab.freqvotat,split.tables = 100)
    message(paste0("Chi-squared = ",round(xtest.crostab$statistic, 2),", df = ",
               xtest.crostab$parameter, ", p-value < ", value.p, "\n"))

    if (prod(dim(table(data[, c(strategy.var, performance.item)]))) == 4) {
        phi.crostab <- psych::phi(table(data[, c(strategy.var, performance.item)]))
        message(paste0("Phi coefficient = ", round(phi.crostab, 4), "\n"))
    }

    #Summary table: continua variables - Summary of  PV1CPRO  by strategy
    for (j in seq(length(tab.freqvotat$Var1))) {
        data2 <- as.data.frame(data[data[, strategy.var] == as.character(tab.freqvotat$Var1[j]), performance.test])
        names(data2) <- performance.test

        if (j == 1) {
            tab.perftest <- as.matrix.data.frame(rbind(round(length(data2[[performance.test]]),0),
                                                       round(min(data2[[performance.test]]),2),
                                                       round(stats::quantile(data2[[performance.test]],
                                                                             probs = 0.25), 2),
                                                       round(stats::median(data2[[performance.test]]), 2),
                                                       round(mean(data2[[performance.test]]), 2),
                                                       round(stats::sd(data2[[performance.test]]), 2),
                                                       round(stats::quantile(data2[[performance.test]],
                                                                             probs = 0.75),2),
                                                       round(max(data2[[performance.test]]), 2)))
            colnames(tab.perftest)[j] <- as.character(tab.freqvotat$Var1[j])
        } else {
            tab.perftest2 <- as.matrix.data.frame(rbind(round(length(data2[[performance.test]]),0),
                                                        round(min(data2[[performance.test]]), 2),
                                                        round(stats::quantile(data2[[performance.test]],
                                                                              probs = 0.25), 2),
                                                        round(stats::median(data2[[performance.test]]), 2),
                                                        round(mean(data2[[performance.test]]), 2),
                                                        round(stats::sd(data2[[performance.test]]), 2),
                                                        round(stats::quantile(data2[[performance.test]],
                                                                              probs = 0.75),2),
                                                        round(max(data2[[performance.test]]), 2)))
            tab.perftest <- cbind(tab.perftest, tab.perftest2)
            colnames(tab.perftest)[j] <- as.character(tab.freqvotat$Var1[j])
        }
    }

    tot.general <- as.matrix.data.frame(rbind(round(length(data[[performance.test]]),0),
                                              round(min(data[[performance.test]]),2) ,
                                              round(stats::quantile(data[[performance.test]],
                                                                    probs = 0.25), 2),
                                              round(stats::median(data[[performance.test]]), 2),
                                              round(mean(data[[performance.test]]), 2),
                                              round(stats::sd(data[[performance.test]]), 2),
                                              round(stats::quantile(data[[performance.test]],
                                                                    probs = 0.75),2),
                                              round(max(data[[performance.test]]), 2)))

    tab.perftest <- cbind(c("Total N", "Min", "1st.Qu", "Median",
                            "Mean", "SD", "3st.Qu", "Max"),
                          tot.general, tab.perftest)
    colnames(tab.perftest) <- c("Statistics", "Total",
                                colnames(tab.perftest)[3:length(colnames(tab.perftest))])

    message("\n Summary of ", performance.test, " by ", strategy.var,
            " - Individual level")
    pander::pandoc.table(tab.perftest, split.tables = 100)
    polyserial.cor <- psych::polyserial(x = as.matrix(data[, performance.test]),
                                        y = as.matrix(data[, strategy.var]))
    message(paste0("Biserial/Polyserial correlation = ",
                   round(polyserial.cor[1], 4), "\n"))
}