ItemFit: Model Fit Functions for Items

In exametrika: Test Theory Analysis and Biclustering

Model Fit Functions for Items

Description

A general function that returns the model fit indices.

Usage

ItemFit(U, Z, ell_A, nparam)

Arguments

U	U is either a data class of exametrika, or raw data. When raw data is given, it is converted to the exametrika class with the dataFormat function.
Z	Z is a missing indicator matrix of the type matrix or data.frame
ell_A	log likelihood of this model
nparam	number of parameters for this model

Value

model_log_like

log likelihood of analysis model

bench_log_like

log likelihood of benchmark model

null_log_like

log likelihood of null model

model_Chi_sq

Chi-Square statistics for analysis model

null_Chi_sq

Chi-Square statistics for null model

model_df

degrees of freedom of analysis model

null_df

degrees of freedom of null model

NFI

Normed Fit Index. Lager values closer to 1.0 indicate a better fit.

RFI

Relative Fit Index. Lager values closer to 1.0 indicate a better fit.

IFI

Incremental Fit Index. Lager values closer to 1.0 indicate a better fit.

TLI

Tucker-Lewis Index. Lager values closer to 1.0 indicate a better fit.

CFI

Comparative Fit Index. Lager values closer to 1.0 indicate a better fit.

RMSEA

Root Mean Square Error of Approximation. Smaller values closer to 0.0 indicate a better fit.

AIC

Akaike Information Criterion. A lower value indicates a better fit.

CAIC

Consistent AIC.A lower value indicates a better fit.

BIC

Bayesian Information Criterion. A lower value indicates a better fit.

exametrika documentation built on Aug. 21, 2025, 5:27 p.m.