Emagnification: A tool for estimating effect-size magnification and performing design calculations in epidemiological studies

Artificial effect-size magnification (ESM) may occur in underpowered studies, where effects are reported only because they or their associated p-value have passed some threshold. Ioannidis (2008) and Gelman and Carlin (2014) have suggested that the plausibility of findings for a specific study can be evaluated by computing ESM, which requires statistical simulation. In this talk, we present a new Stata package, emagnification, that allows straightforward implementation of such simulations in Stata. The commands automate these simulations for epidemiological studies and enable the user to assess ESM routinely for published studies using user-selected, study-specific inputs that are commonly reported in published literature. The intention of the package is to allow a wider community to use ESMs as a tool for evaluating the reliability of reported effect sizes and to put an observed statistically significant effect size into a fuller context with respect to potential implications for study conclusions.