Into the multiverse: Conducting and visualizing multiverse analysis in Stata

Multiverse analysis is becoming an important tool in the methodological repertoire of social scientists. The idea behind the method—variously referred to as “multiverse analysis”, “multimodel analysis”, “specification curve analysis”, or “vibration of effects”—is straightforward: because there are many credible ways of formulating an analysis, and any single statistical estimate may suffer from selective reporting, multiverse analysis explores all reasonable specifications, contrasting authors’ preferred estimates with a range of possible estimates. Instead of luring readers into a dark corner of the “garden of forking paths”, multiverse analysis provides a bird’s-eye view of the maze of researcher decisions and the resulting range of defensible findings. While multiverse analysis holds significant promise for quantitative empirical research, it poses conceptual, computational, and practical challenges. This talk provides a primer on implementing multiverse analysis in Stata. It highlights the strengths and limitations of existing multiverse tools (for example, mrobust and multivrs) and introduces a new plot type designed to visualize multiverse results effectively. By addressing key challenges in conducting and visualizing multiverse results, the talk seeks to encourage Stata users to adopt multiverse analysis and unlock its potential for robust and transparent research.