CDM: predict – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

predict

Expected Values and Predicted Probabilities from Item Response Response Models

Description

This function computes expected values for each person and each item based on the individual posterior distribution. The output of this function can be the basis of creating item and person fit statistics.

Usage

IRT.predict(object, dat, group=1)

## S3 method for class 'din'
predict(object, group=1, ...)

## S3 method for class 'gdina'
predict(object, group=1, ...)

## S3 method for class 'mcdina'
predict(object, group=1, ...)

## S3 method for class 'gdm'
predict(object, group=1, ...)

## S3 method for class 'slca'
predict(object, group=1, ...)

Arguments

`object`	Object for the S3 methods `IRT.irfprob` and `IRT.posterior` are defined. In the CDM packages, these are the objects of class `din`, `gdina`, `mcdina`, `slca` or `gdm`.
`dat`	Dataset with item responses
`group`	Group index for use
`...`	Further arguments to be passed.

Value

A list with following entries

`expected`	Array with expected values (persons \times classes \times items)
`probs.categ`	Array with expected probabilities for each category (persons \times categories \times classes \times items)
`variance`	Array with variance in predicted values for each person and each item.
`residuals`	Array with residuals for each person and each item
`stand.resid`	Array with standardized residuals for each person and each item

Examples

## Not run: 
#############################################################################
# EXAMPLE 1: Fitted Rasch model in TAM package
#############################################################################

#--- Model 1: Rasch model
library(TAM)
mod1 <- TAM::tam.mml(resp=TAM::sim.rasch)
# apply IRT.predict function
prmod1 <- CDM::IRT.predict(mod1, mod1$resp )
str(prmod1)

## End(Not run)

#############################################################################
# EXAMPLE 2: Predict function for din
#############################################################################

# DINA Model
mod1 <- CDM::din( CDM::sim.dina, q.matr=CDM::sim.qmatrix, rule="DINA" )
summary(mod1)
# apply predict method
prmod1 <- CDM::IRT.predict( mod1, sim.dina )
str(prmod1)

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