Concern over the validity of statistical tests performed on data that may not satisfy underlying assumptions has prompted methodological researchers to perform Monte Carlo studies for frequently used tests. Unfortunately, these studies appear to have had little impact on methodological practice. One reason is the lack of an overarching framework to guide the interpretation of Monte Carlo studies for the same test. Another is the impressionistic nature of these studies, which can lead different readers to different conclusions. These shortcomings can be addressed using quantitative methods of research synthesis (e.g., meta-analysis) to summarize the results of Monte Carlo studies for a statistical test. In this paper, these methods are applied to a sample of Monte Carlo studies of the F-test in the oneway fixed-effects analysis of variance (ANOVA) model. The present analyses were based on Monte Carlo studies reported in 21 out of 30 journal articles. The results provide empirical support for the robustness of the Type I error rate of the F-test to certain assumption violations. However, the Type I error rate of the F-test was noticeably affected by unequal variances, even when sample sizes were equal. Recommendations for using this test when certain assumptions are violated are made. Four data tables and one bar graph are included. (Author/TJH)