The CALIS Procedure

FITINDEX Statement

  • FITINDEX option <option …>;

You can use the FITINDEX statement to set the options for computing and displaying the fit indices, or to output the fit indices. All but the OFF= and ON= options of the FITINDEX statement are also available in the PROC CALIS statement. The options set in the FITINDEX statement will overwrite those set in the PROC CALIS statement.

For the listing of fit indices and their definitions, see the section Overall Model Fit Indices. Note that not all fit indices are available with all estimation methods, which is specified by the METHOD= option of the PROC CALIS statement. See the section Fit Indices and Estimation Methods for more details.

The options of the FITINDEX statement are as follows:

ALPHAECV=$\alpha $

specifies a $(1-\alpha )100\% $ confidence interval ($0 \leq \alpha \leq 1$) for the Browne and Cudeck (1993) expected cross validation index (ECVI). See the ALPHAECV= option of the PROC CALIS statement .

ALPHARMS=$\alpha $

specifies a $(1-\alpha )100\% $ confidence interval ($0 \leq \alpha \leq 1$) for the Steiger and Lind (1980) root mean square error of approximation (RMSEA) coefficient. See the ALPHARMS= option of the PROC CALIS statement .

BASEFIT=SAS-data-set
INBASEFIT=SAS-data-set

inputs the SAS-data-set that contains the fit information of the baseline model of your choice. See the BASEFIT= option of the PROC CALIS statement .

BASEFUNC=r(<DF=>i)
BASEFUNC(<DF=>i)=r

inputs the fit function value r and the degrees of freedom i of the baseline model of your choice. See the BASEFUNC= option of the PROC CALIS statement .

CHICORRECT= name  |  c
CHICORR= name  |  c

specifies a correction factor c for the chi-square statistics for model fit. See the CHICORRECT= option of the PROC CALIS statement .

CLOSEFIT=p

defines the criterion value p for indicating a close fit. See the CLOSEFIT= option of the PROC CALIS statement .

DFREDUCE=i

reduces the degrees of freedom of the $\chi ^2$ test by i. See the DFREDUCE= option of the PROC CALIS statement .

NOADJDF

turns off the automatic adjustment of degrees of freedom when there are active constraints in the analysis. See the NOADJDF option of the PROC CALIS statement .

NOINDEXTYPE

disables the display of index types in the fit summary table. See the NOINDEXTYPE option of the PROC CALIS statement .

OFF= [names]  |  {names}
OFFLIST= [names]  |  {names}

turns off the printing of one or more fit indices or modeling information as indicated by names, where a name represents a fit index, a group of fit indices, or modeling information. Names must be specified inside a pair of parentheses and separated by spaces. By default, all fit indices are printed. See the ON= option for the value of names.

ON < (ONLY) > = [names]  |  {names}
ONLIST < (ONLY) > = [names]  |  {names}

turns on the printing of one or more fit indices or modeling information as indicated by names, where a name represents a fit index, a group of fit indices, or modeling information. Names must be specified inside a pair of parentheses and separated by spaces. Because all fit indices and modeling information are printed by default, using an ON= list alone is redundant. When both ON= and OFF= lists are specified, the ON= list will override the OFF= list for those fit indices or modeling information that appear on both lists. If an ON(ONLY)= list is used, only those fit indices or modeling information specified in the list will be printed. Effectively, an ON(ONLY)= list is the same as the specification with an ON= list with the same selections and an OFF=ALL list in the FITINDEX statement.

Output Control of Fit Index Groups and Modeling Information GroupYou can use the following names to refer to the groups of fit indices or modeling information available in PROC CALIS:

ABSOLUTE

Absolute or stand-alone fit indices that measures the model fit without using a baseline model.

ALL

All fit indices available in PROC CALIS.

INCREMENTAL

Incremental fit indices that measure model fit by comparing with a baseline model.

MODELINFO

General modeling information including sample size, number of variables, number of variables, and so on.

PARSIMONY

Fit indices that take model parsimony into account.

Output Control of Modeling InformationYou can use the following names to refer to the individual modeling information available in PROC CALIS:

BASECHISQ

Chi-square statistic for the baseline model.

BASEDF

Degrees of freedom of the chi-square statistic for the baseline model.

BASEFUNC

Baseline model function value.

BASELOGLIKE

Baseline model –2 log-likelihood function value for METHOD=FIML.

BASEPROBCHI

p-value of the chi-square statistic for the baseline model fit.

BASESTATUS

Status of the baseline model fitting for METHOD=FIML.

NACTCON

Number of active constraints.

NIOBS

Number of incomplete observations for METHOD=FIML.

NMOMENTS

Number of elements in the moment matrices being modeled.

NOBS

Number of observations assumed in the analysis.

NPARM | NPARMS

Number of independent parameters.

NVAR

Number of variables.

SATFUNC

Saturated model function value for METHOD=FIML.

SATLOGLIKE

Saturated model –2 log-likelihood function value for METHOD=FIML.

SATSTATUS

Status of the saturated model fitting for METHOD=FIML.

Output Control of Absolute Fit IndicesYou can use the following names to refer to the individual absolute fit indices available in PROC CALIS:

CHISQ

Chi-square statistic for model fit.

CN | CRITICAL_N

Hoelter’s critical N.

CONTLIKE

Percentage contribution to the Log-likelihood function value of each group in multiple-group analyses with METHOD=FIML.

CONTRIBUTION | CONTCHI

Percentage contribution to the chi-square value for multiple-group analyses.

DF

Degrees of freedom for the chi-square test for model fit.

ELLIPTIC

Elliptical chi-square statistic for ML and GLS methods in single-group analyses without mean structures. This index is computed only when you input the raw data with the KURTOSIS option specified.

FUNCVAL

Optimized function value.

GFI

Goodness-of-fit index by Jöreskog and Sörbom.

LOGLIKE

Fitted model –2 log-likelihood function value for METHOD=FIML.

PROBCHI

P-value of the chi-square statistic for model fit.

PROBELLIPTIC

P-value of the elliptical chi-square statistic.

RMR

Root mean square residual.

SRMR

Standardized root mean square residual.

ZTEST

Z-test of Wilson and Hilferty.

Output Control of Parsimonious Fit IndicesYou can use the following names to refer to the individual parsimonious fit indices available in PROC CALIS:

AGFI

Adjusted GFI.

AIC

Akaike information criterion.

CAIC

Bozdogan corrected AIC.

CENTRALITY

McDonald centrality measure.

ECVI

Expected cross-validation index.

ECVI_LL | LL_ECVI

Lower confidence limit for ECVI.

ECVI_UL | UL_ECVI

Upper confidence limit for ECVI.

PGFI

Parsimonious GFI.

PROBCLFIT

Probability of close fit.

RMSEA

Root mean square error of approximation.

RMSEA_LL | LL_RMSEA

Lower confidence limit for RMSEA.

RMSEA_UL | UL_RMSEA

Upper confidence limit for RMSEA.

SBC

Schwarz Bayesian criterion.

Output Control of Incremental Fit IndicesYou can use the following names to refer to the individual incremental fit indices available in PROC CALIS:

BENTLERCFI | CFI

Bentler comparative fit index.

BENTLERNFI

Bentler-Bonett normed fit index.

BENTLERNNFI

Bentler-Bonett nonnormed fit index.

BOLLENNFI

Bollen normed fit index (Rho1).

BOLLENNNFI

Bollen nonnormed fit index (Delta2).

PNFI

James et al. parsimonious normed fit index.

OUTFIT=SAS-data-set

creates an output data set containing the values of the fit indices. This is the same as the OUTFIT= option of the PROC CALIS statement . See the section OUTFIT= Data Set for details.