Simulate from Generalized Logistic Item Response Model
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.
sim.raschtype(theta, b, alpha1=0, alpha2=0, fixed.a=NULL,
    fixed.c=NULL, fixed.d=NULL)| theta | Unidimensional ability vector θ | 
| b | Vector of item difficulties b | 
| alpha1 | Parameter α_1 in generalized logistic link function | 
| alpha2 | Parameter α_2 in generalized logistic link function | 
| fixed.a | Vector of item slopes a | 
| fixed.c | Vector of lower item asymptotes c | 
| fixed.d | Vector of lower item asymptotes d | 
The class of generalized logistic link functions contain the most important link functions using the specifications (Stukel, 1988):
logistic link function: α_1=0 and α_2=0 
probit link function: α_1=0.165 and α_2=0.165 
loglog link function: α_1=-0.037 and α_2=0.62 
cloglog link function: α_1=0.62 and α_2=-0.037 
See pgenlogis for exact transformation formulas of
the mentioned link functions.
Data frame with simulated item responses
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.
############################################################################# ## 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 )
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