The Type I error rates and statistical power of nine selected multiple comparison procedures were compared in a Monte Carlo study. The Peretz, Ryan, and Fisher-Hayter tests were the most powerful, and differences among these procedures were consistently small. Choosing among these procedures might be based on their calculational complexity. (SLD)

The purpose of this study was to investigate and compare the performance of a stepwise variable selection algorithm to traditional exploratory factor analysis. The Monte Carlo study included six factors in the design; the number of common factors; the number of variables explained by the common factors; the magnitude of factor loadings; the number…

The performance of methods for detecting publication bias in meta-analysis was evaluated using Monte Carlo methods. Four methods of bias detection were investigated: Begg's rank correlation, Egger's regression, funnel plot regression, and trim and fill. Five factors were included in the simulation design: number of primary studies in each…

A Monte Carlo study was conducted to estimate the small sample standard errors and statistical bias of psychometric statistics commonly used in the analysis of achievement tests. The statistics examined in this research were: (1) the index of item difficulty; (2) the index of item discrimination; (3) the corrected item-total point-biserial…

A Monte Carlo study was conducted to compare the performance of three statistical indices of test item bias in small samples of examinees. The statistical indices compared were the Delta method, the Mantel-Haenszel (MH) method, and the Standardization method. Sample sizes of 50, 100, and 200 were examined. One thousand samples of each size were…