The purpose of this study was to investigate the effects of sample size on the power of five selected fit indices through a Monte Carlo simulation. Two models (a reduced and a complete model) and 6 sample sizes (20, 50, 100, 200, 500, and 1,000) were used to investigate the effect on the power of fit indices as the sample size was varied. The power of the selected fit indices, more often than not, was different across sample sizes, indicating that sample size does affect the power of the fit indices. The results of this study indicate that of all the indices examined, the Goodness of Fit Index (GFI) was the most powerful fit index. (Contains 2 tables, 4 figures, and 26 references.) (Author/SLD)