Abstract
A major issue in the utilization of covariance structure analysis is model fit evaluation. Recent years have witnessed increasing interest in various test statistics and so-called fit indexes, most of which are actually based on or closely related to F 0, a measure of model fit in the population. This study aims to provide a systematic investigation about the performance of 4 available estimators of F 0. [Fcirc]01 is the conventional estimator and is based on noncentral chi-square approximation. [Fcirc]02 is newly proposed and does not assume noncentral chi-square approximation. [Fcirc]03 and [Fcirc]04 are variations of [Fcirc]02. A Monte Carlo simulation study is conducted to examine how these four estimators of F 0 perform across varying model misspecifications, data distributions, model sizes, and sample sizes. The results show that under normality all 4 quantities estimate F 0 equally well, and under nonnormality [Fcirc]02, [Fcirc]03, and [Fcirc]04 outperform [Fcirc]01. Issues related to these findings are discussed.
ACKNOWLEDGMENTS
I wish to thank Ke-Hai Yuan, Scott Maxwell, and Steve Boker for their helpful comments on an earlier version of this article.