sim.raschtype {sirt}R Documentation

Simulate from Generalized Logistic Item Response Model

Description

This function simulates dichotomous item responses from a generalized logistic item response model (Stukel, 1988). The four-parameter logistic item response model (Loken & Rulison, 2010) is a special case. See rasch.mml2 for more details.

Usage

sim.raschtype(theta, b, alpha1=0, alpha2=0, fixed.a=NULL,
    fixed.c=NULL, fixed.d=NULL)

Arguments

theta

Unidimensional ability vector θ\theta

b

Vector of item difficulties bb

alpha1

Parameter α1\alpha_1 in generalized logistic link function

alpha2

Parameter α2\alpha_2 in generalized logistic link function

fixed.a

Vector of item slopes aa

fixed.c

Vector of lower item asymptotes cc

fixed.d

Vector of lower item asymptotes dd

Details

The class of generalized logistic link functions contain the most important link functions using the specifications (Stukel, 1988):

logistic link function: α1=0\alpha_1=0 and α2=0\alpha_2=0
probit link function: α1=0.165\alpha_1=0.165 and α2=0.165\alpha_2=0.165
loglog link function: α1=0.037\alpha_1=-0.037 and α2=0.62\alpha_2=0.62
cloglog link function: α1=0.62\alpha_1=0.62 and α2=0.037\alpha_2=-0.037

See pgenlogis for exact transformation formulas of the mentioned link functions.

Value

Data frame with simulated item responses

References

Loken, E., & Rulison, K. L. (2010). Estimation of a four-parameter item response theory model. British Journal of Mathematical and Statistical Psychology, 63, 509-525.

Stukel, T. A. (1988). Generalized logistic models. Journal of the American Statistical Association, 83, 426-431.

See Also

rasch.mml2, pgenlogis

Examples

#############################################################################
## EXAMPLE 1: Simulation of data from a Rasch model (alpha_1=alpha_2=0)
#############################################################################

set.seed(9765)
N <- 500    # number of persons
I <- 11     # number of items
b <- seq( -2, 2, length=I )
dat <- sirt::sim.raschtype( stats::rnorm( N ), b )
colnames(dat) <- paste0( "I", 1:I )

[Package sirt version 4.1-15 Index]