calc Fit Indices

A general function that returns the model fit indices.

Usage

calcFitIndices(chi_A, chi_B, df_A, df_B, nobs)

Arguments

chi_A

chi-squares for this model

chi_B

chi-squares for compared model

df_A

degrees of freedom for this model

df_B

degrees of freedom for compared model

nobs

number of observations for Information criteria

Value

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.

Note

This is an internal helper that turns the chi-square statistics of the analysis and benchmark models into fit indices. It will no longer be exported in exametrika 3.0.0; use the TestFitIndices element of a fitted model, or M2(), instead.