IRT.classify: Individual Classification for Fitted Models

In alexanderrobitzsch/CDM: Cognitive Diagnosis Modeling

Individual Classification for Fitted Models

Description

Computes individual classifications based on a fitted model.

Usage

IRT.classify(object, type="MLE")

Arguments

object	Fitted model for which methods IRT.likelihood and IRT.posterior are defined.
type	Type of classification: "MLE" (maximum likelihood estimate) or "MAP" (maximum of posterior distribution)

Value

List with entries

class_theta	Individual classification
class_index	Class index of individual classification
class_maxval	Maximum value corresponding to individual classification

See Also

See IRT.factor.scores for similar functionality.

Examples

## Not run: 
#############################################################################
# EXAMPLE 1: Individual classification data.ecpe
#############################################################################

data(data.ecpe, package="CDM")
dat <- data.ecpe$dat[,-1]
Q <- data.ecpe$q.matrix

#** estimate GDINA model
mod <- CDM::gdina(dat, q.matrix=Q)
summary(mod)

#** classify individuals
cmod <- CDM::IRT.classify(mod)
str(cmod)

## End(Not run)

alexanderrobitzsch/CDM documentation built on July 3, 2024, 7:42 p.m.