# Plot probability and surprisal curves for test or scale items. ICC_plot plots each item in argument `plotindex` in turn after function`Sbinsmth()` has used spline smoothing to estimate item and option characteristic curves. ```r ICC_plot(scrfine, SfdList, dataList, Qvec, binctr=NULL, data_point = FALSE, ci = FALSE, plotType="S", Srng=c(0,5), DSrng=c(-0.2, 0.2), plotindex=1:n, titlestr = NULL, itemscopevec = rep(0, length(plotindex)), plotTitle = TRUE,autoplot = FALSE, plotMissing = TRUE, plotrange=c(min(scrfine),max(scrfine)), shaderange = NULL, ttlsz = NULL, axisttl = NULL, axistxt = NULL, lgdlab = NULL, lgdpos = "bottom") ``` ## Arguments - `scrfine`: A vector of 101 plotting points. - `SfdList`: A numbered list object produced by a TestGardener analysis of a test. Its length is equal to the number of items in the test or questions in the scale. Each member of `SfdList` is a named list containing information computed during the analysis. - `dataList`: A list that contains the objects needed to analyse the test or rating scale. - `Qvec`: A vector of five marker percentile values. For plotting over information, this is replaced by Qinfovec returned as parmList$Qinfovec. - `binctr`: A vector of bin center values. If the plot is over arc length or information, `binctr` is modified before calling `Sbinsth_plot` by the command `binctrinfo = pracma::interp1(indfine, alfine, binctr)`, and argument `binctr` is replaced by `binctrinfo`. - `data_point`: A logical value indicating whether to plot the data points. - `ci`: A logical value indicating whether to plot the confidence limits. - `plotType`: Type(s) of plot, default as "P" for probability, can also be "S" for surprisal, "DS" for sensitivity, and any combination of the three - `Srng`: A vector of length 2 specifing the plotting range for surprisal values. - `DSrng`: A vector of length 2 specifing the plotting range for sensitivity values. - `plotindex`: A vector of indices of items to be plotted. - `titlestr`: plot title - `itemscopevec`: A numeric vector containing item scope values. - `plotTitle`: indicator of showing the plot title, default as TRUE - `autoplot`: indicator for plotting all items in a batch - `plotMissing`: Determine if plot the extra option for missing/spoiled responses. - `plotrange`: A vector of length 2 containing the plot boundaries of the score index interval. - `shaderange`: a list of length 2 vector(s); set if users want to gray out specific score range(s) - `ttlsz`: Title font size. - `axisttl`: Axis title font size. - `axistxt`: Axis text(tick label) font size. - `lgdlab`: Legend label font size. - `lgdpos`: legend position, could be set as "None" to remove the legend. ## Returns A list vector is returned which is of the length of argument `plotindex`. Each member of the vector is a `gg` or `ggplot` object for the associated `plotindex value`. Each plot can be displayed using the `print` command. The plots of item power are produced as a side value even if no output object is specified in the call to the function. ## References Ramsay, J. O., Li J. and Wiberg, M. (2020) Full information optimal scoring. Journal of Educational and Behavioral Statistics, 45, 297-315. Ramsay, J. O., Li J. and Wiberg, M. (2020) Better rating scale scores with information-based psychometrics. Psych, 2, 347-360. ## Author(s) Juan Li and James Ramsay ## See Also `ICC`, `Sensitivity_plot`, `Power_plot`, `Entropy_plot`, `Sbinsmth` ## Examples ```r # Example 1. Display the item surprisal curves for the # short SweSAT multiple choice test with 24 items and 1000 examinees dataList <- Quant_13B_problem_dataList SfdList <- Quant_13B_problem_parmList$SfdList Qvec <- Quant_13B_problem_parmList$Qvec binctr <- Quant_13B_problem_parmList$binctr infoSurpvec <- Quant_13B_problem_infoList$infoSurpvec Qinfovec <- Quant_13B_problem_infoList$Qinfovec bininfoctr <- Quant_13B_problem_infoList$bininfoctr titlestr <- "Quant_13B_problem" # plot the curves for the first question over the score index oldpar <- par(no.readonly=TRUE) indfine <- seq(0,100,len=101) ICC_plot(indfine, SfdList, dataList, Qvec, binctr, data_point = TRUE, plotType = c("S", "P"), Srng=c(0,4), plotindex=1) # plot the curves for the first question over test information ICC_plot(infoSurpvec, SfdList, dataList, Qinfovec, bininfoctr, data_point = TRUE, plotType = c("S", "P"), Srng=c(0,4), plotindex=1) par(oldpar) ```

ICC_plot function