IC: Information criteria

In eRm: Extended Rasch Modeling

Information criteria

Description

Computation of information criteria such as AIC, BIC, and cAIC based on unconditional (joint), marginal, and conditional log-likelihood

Usage

## S3 method for class 'ppar'
IC(object)

Arguments

object

Object of class ppar (from person.parameter().

Details

The joint log-likelihood is established by summation of the logarithms of the estimated solving probabilities. The marginal log-likelihood can be computed directly from the conditional log-likelihood (see vignette for details).

Value

The function IC returns an object of class ICr containing:

ICtable

Matrix containing log-likelihood values, number of parameters, AIC, BIC, and cAIC for the joint, marginal, and conditional log-likelihood.

See Also

LRtest.Rm

Examples

#IC's for Rasch model
res <- RM(raschdat2)             #Rasch model
pres <- person.parameter(res)    #Person parameters
IC(pres)

#IC's for RSM
res <- RSM(rsmdat)
pres <- person.parameter(res)
IC(pres)

eRm documentation built on May 29, 2024, 2:12 a.m.