generate_irtree_2012: Generate data for Boeckenholt Model.

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

Description

Function generates categorical data 1...5 for N persons and J items given the item parameters betas.

Usage

generate_irtree_2012(N = NULL, J = NULL, betas = NULL,
  traitItem = rep(1, J), theta_vcov = NULL, prop.rev = 0.5,
  revItem = NULL, cat = TRUE)

Arguments

N	number of persons
J	number of items
betas	Jx3 matrix with item parameters on three response dimensions (middle, extreme, target trait defined by traitItem).
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)
theta_vcov	3x3 covariance matrix for middle, extremity, trait(s) (can be a vector of length 3 with variances for uncorrelated processes).
prop.rev	proportion of reversed items (rounded to next integer). Can be a vector if multiple traits are specified by traitItem. Only used if revItem = NULL.
revItem	vector of length J specifying reversed items (1=reversed, 0=regular)
cat	whether to return categorical data (response categories 1...5) or multinomial data (frequencies of 0 and 1)

Value

The function returns a list containing the generated matrix of responses X, a vector revItem indicating reversed items and true, latent values of the parameters.

Examples

N <- 20
J <- 10
betas <- cbind(rnorm(J, .5), rnorm(J, .5), rnorm(J, 0))
dat <- generate_irtree_2012(N = N, J = J, betas = betas)

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