We address a methodological issue of the evaluation of the difference in effects in epidemiological studies that may arise, for example, from stratum-specific analyses or differences in analytical decisions during data analysis. We propose a new simulation-based method to quantify the plausible extent of such heterogeneity, rather than testing a hypothesis about its existence. We examine the contribution of the method to the debate surrounding risk of multiple myeloma and glyphosate use and propose that its application contributes to a more balanced weighting of evidence.
Keywords: effect size; epidemiology; homogeneity; simulation.