Monte Carlo studies of statistical tests are prominently featured in the methodological research literature. Unfortunately, the information from these studies does not appear to have significantly influenced methodological practice in educational and psychological research. One reason is that Monte Carlo studies lack an overarching theory to guide their interpretation. Also, the impressionistic nature of Monte Carlo studies can lead different readers to different conclusions. These shortcomings can be addressed using meta-analytic methods to summarize the results of Monte Carlo studies. Summarizing Monte Carlo studies in this fashion will generate guidelines for the appropriate use of particular statistical tests under specific assumption violations, and will allow an evaluation of the validity of the statistical results of previously published studies. This paper provides a methodological framework for, and an example of, quantitatively summarizing empirical Type I error and power values from Monte Carlo studies. The four-step summarization strategy covers problem formulation, data collection, data evaluation, and data analysis and interpretation. The example of a quantitative summary involves seven Monte Carlo studies of the parametric Bartlett test of the quality of independent variances. (Author/TJH)