A Bootstrap Procedure for Evaluating Goodness-of-Fit Indices of Structural Equation and Confirmatory Factor Models

Abstract

The authors propose a bootstrap procedure for evaluating the goodness-of-fit indices for structural equation and confirmatory factor models. Monté Carlo simulations are applied to obtain a bootstrap sampling distribution (BSD) for each fit statistic. Then the BSD is used to evaluate model fit. Because the BSD takes into consideration sample size and model characteristics (e.g., number of factors, number of indicators per factor), its application in the proposed procedure makes it possible to compare the fits of competing models. Two previous studies are reanalyzed in illustrating how to implement the proposed procedure.