plot_responses: Plot observed frequencies.

In hplieninger/mpt2irt: Bringing Multinomial Processing Tree Models To Item Response Theory To Investigate Response Styles

Description

Plot histograms of observed response frequencies separately for each item. This is especially helpful to judge whether simulated data are reasonable (i.e., unimodal etc.).

Usage

plot_responses(X, revItem = rep(0, ncol(X)), traitItem = rep(1,
  ncol(X)), points = 5, ...)

Arguments

X	an N x J matrix of observed responses for categories 1...5 (use mult_to_cat to transform a multinomial frequency matrix with 1s/0s to responses from 1...5)
revItem	vector of length J specifying reversed items (1=reversed, 0=regular)
traitItem	vector of length J specifying the underlying traits (e.g., indexed from 1...5). Standard: only a single trait is measured by all items. If the Big5 are measured, might be something like c(1,1,1,2,2,2,...,5,5,5,5)
points	how many resposne categories in Likert scale
...	Additional arguments passed to barplot.

Examples

## Not run: 
  N <- 20
  J <- 10
  betas <- cbind(rnorm(J, .5), rnorm(J, .5), rnorm(J, 1.5), rnorm(J, 0))
  dat <- generate_irtree_ext(N = N, J = J, betas = betas, beta_ARS_extreme = .5)
  plot_responses(dat$X, revItem = dat$revItem, traitItem = dat$traitItem)

## End(Not run)

hplieninger/mpt2irt documentation built on May 17, 2019, 4:54 p.m.