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library(knitr) library(rpf) library(ggplot2) library(reshape2) library(gridExtra) opts_chunk$set(echo=FALSE)
This template is suitable for plotting a single group of 1 dimensional items. Refer to the Rmd source code to see how to adapt this template to your project.
Normally you would obtain model parameters from OpenMx (or flexMIRT with flexmirt.read), but here are some inline parameters for demonstration purposes.
small <- structure(list(param = structure(c(1, 1, 0, 0, -0.5789195, -2.412259, -1.3471789, 1, 1, 0, 0, 1.0983234, -2.0991327, -2.9482965, 1, 1, 0, 0, 0.4078264, -0.9824549, -1.5905594, 1, 1, 0, 0, -1.0650001, -0.2100243, -3.2034577), .Dim = c(7L, 4L), .Dimnames = list(NULL, c("X2", "X6", "X7", "X10"))), mean = 0, cov = structure(9.8238066, .Dim = c(1L, 1L))), .Names = c("param", "mean", "cov")) small$spec <- list() small$spec[1:4] <- rpf.nrm(outcomes=4, T.c= lower.tri(diag(3),TRUE) * -1)
width <- 5 small$icc <- list() small$iif <- list() tcc <- expand.grid(theta=seq(-width,width,.1), score=0) tic <- expand.grid(theta=seq(-width,width,.1), info=0) for (ix in 1:length(small$spec)) { name <- colnames(small$param)[ix] ii <- small$spec[[ix]] ii.p <- small$param[,ix] grid <- expand.grid(theta=seq(-width,width,.1)) grid <- cbind(grid, t(rpf.prob(ii, ii.p, grid$theta))) tcc$score <- tcc$score + c(0:(ii@outcomes-1) %*% rpf.prob(ii, ii.p, grid$theta)) colnames(grid) <- c("theta", paste0("k", 0:3)) grid2 <- melt(grid, id.vars=c("theta"), variable.name="category", value.name="p") small$icc[[ix]] <- ggplot(grid2, aes(theta, p, color=category)) + geom_line() + ggtitle(paste("Item", name)) + ylim(0,1) + xlim(-width, width) grid <- expand.grid(theta=seq(-width,width,.1)) grid$info <- rpf.info(ii, ii.p, t(grid$theta)) tic$info <- tic$info + grid$info small$iif[[ix]] <- ggplot(grid, aes(theta, info)) + geom_line() + ggtitle(paste("Item", name)) + xlim(-width, width) } do.call(grid.arrange, c(small$icc, ncol=2))
do.call(grid.arrange, c(small$iif, ncol=2))
tcc.plot <- ggplot(tcc, aes(theta, score)) + geom_line() + ggtitle("Test Characteristic Curve") + xlim(-width, width) tic.plot <- ggplot(tic, aes(theta, info)) + geom_line() + ggtitle("Test Information Curve") + xlim(-width, width) grid.arrange(tcc.plot, tic.plot, ncol=2)
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