CDM: sim_model – R documentation

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sim_model

Simulate an Item Response Model

Description

Simulates an item response model given a fitted object or input of item response probabilities and skill class probabilities.

Usage

sim_model(object=NULL, irfprob=NULL, theta_index=NULL, prob.theta=NULL,
      data=NULL, N_sim=NULL )

Arguments

`object`	Fitted object for which the methods `IRT.posterior`, and `IRT.data` are defined.
`irfprob`	Array of item response function values (items \times categories \times skill classes)
`theta_index`	Skill class index for sampling
`prob.theta`	Skill class probabilities
`data`	Original dataset, only relevant for simulating item response pattern with missing values
`N_sim`	Number of subjects to be simulated

Value

List containing elements

`dat`	Simulated item responses
`theta`	Simulated skill classes
`theta_index`	Corresponding indices to `theta`

Examples

## Not run: 
#############################################################################
# EXAMPLE 1: GDINA model simulation
#############################################################################

data(sim.dina, package="CDM")
data(sim.qmatrix, package="CDM")
dat <- sim.dina
Q <- sim.qmatrix

# fit DINA model
mod <- CDM::gdina( dat, q.matrix=Q, rule="DINA")
summary(mod)

#** simulate new item responses (N equals observed sample size)
dat1 <- CDM::sim_model(mod)

#*** simulate item responses for N=2000 subjects
dat2 <- CDM::sim_model(mod, N_sim=2000)
str(dat2)

#*** simulate item responses based on input item response probabilities
#*** and theta_index
irfprob <- CDM::IRT.irfprob(mod)
prob.theta <- attr(irfprob, "prob.theta")
TP <- length(prob.theta)
theta_index <- sample(1:TP, size=1000, prob=prob.theta, replace=TRUE )
#-- simulate
dat3 <- CDM::sim_model(irfprob=irfprob, theta_index=theta_index)
str(dat3)

## End(Not run)

CDM

Cognitive Diagnosis Modeling

v7.5-15

GPL (>= 2)

Authors

Alexander Robitzsch [aut, cre], Thomas Kiefer [aut], Ann Cathrice George [aut], Ali Uenlue [aut]

Initial release

2020-03-10 14:19:21