Meta-analysis for integrating study outcomes: A Monte Carlo study of its susceptibility to Type I and Type II errors.

A Monte Carlo study was conducted to determine Types I and II error rates of the Schmidt and Hunter (S&H) meta-analysis method and the U statistic for assessing homogeneity within a set of correlations. One thousand samples of correlations were generated randomly to fill each of 450 cells of an 18 × 5 × 5 (Underlying Population Correlations × Numbers of Correlations Compared × Sample Size Per Correlation) design. To assess Type I error rates, correlations were drawn from the same population. To assess power, correlations were drawn from two different populations. As compared with U, which was uniformly robust, the Type I error rate for the S&H method was unacceptably high in many cells, particularly when the criterion for determining homogeneity was set at a highly conservative level. Power for the S&H method increased with increasing size of population differences, sample size per correlation, and in some cases, number of correlations compared. The U statistic did more poorly in most conditions in protecting from Type II errors.