rpl: Simulate Data under a Parametric Logistic IRT Model

View source: R/nplmodel.R

rplR Documentation

Simulate Data under a Parametric Logistic IRT Model

Description

rpl simulates IRT data under a parametric logistic IRT model of type "2PL", "3PL", "3PLu", "4PL", and "Rasch/1PL".

Usage

rpl(theta, a = NULL, b, g = NULL, u = NULL, return_setting = TRUE)

Arguments

theta

numeric vector of person parameters. Can also be a list, then a list of length length(theta) is returned, containing multiple simulated data matrices.

a

numeric vector of item discrimination parameters. If NULL, by default set to a vector of ones of length length(b).

b

numeric vector of item difficulty parameters.

g

numeric vector of so-called item guessing parameters. If NULL, by default set to a vector of zeroes of length length(b).

u

numeric vector of item upper asymptote parameters. If NULL, by default set to a vector of ones of length length(b).

return_setting

logical. Should a list containing slots of "a", "b", "g", "u", and "theta", as well as the simulated data matrix "data" be returned (default) or only the simulated data matrix.

Value

rpl returns either a list of the following components:

a

numeric vector of item discrimination parameters used,

b

numeric vector of item difficulty parameters used,

g

numeric vector of item guessing parameters used,

u

numeric vector of item upper asymptote parameters used,

theta

numeric vector of person parameters used,

data

numeric matrix containing the simulated data,

or (if return_setting = FALSE) only the numeric matrix containing the simulated data.

See Also

rrm, rgpcm, rpcm, rrsm

Examples

set.seed(1)
## item responses under a 2PL (two-parameter logistic) model from
## 6 persons with three different person parameters
## 9 increasingly difficult items and corresponding discrimination parameters
## no guessing (= 0) and upper asymptote 1
ppar <- rep(c(-2, 0, 2), each = 2)
ipar <- seq(-2, 2, by = 0.5)
dpar <- rep(c(0.5, 1, 1.5), each = 3)
sim <- rpl(theta = ppar, a = dpar, b = ipar)

## simulated item response data along with setting parameters
sim

## print and plot corresponding item response object
iresp <- itemresp(sim$data)
iresp
plot(iresp)

psychotools documentation built on May 29, 2024, 8:12 a.m.