Replication Data for: A Practical Guide to Dealing with Attrition in Political Science Experiments

Despite admonitions to address attrition in experiments - missingness on Y - alongside best practices designed to encourage transparency, most political science researchers all but ignore it. A quantitative literature search of this journal - where we’d expect to find the most conscientious reporting of attrition - shows low rates of discussion of the issue. We suspect that there are few options to convincingly demonstrate low or less-concerning attrition when this occurs, confusion on the link between when attrition occurs and the type of validity it threatens when it does occur, and limited connection to and guidance on which estimands are threatened by different attrition patterns. This is exacerbated by limited tools to identify, investigate and report types of attrition. We offer the R package attritevis - to visualize attrition over time, by intervention, and include a step-by-step guide to identifying and addressing attrition that balances post-hoc analytical tools with guidance for revising designs to ameliorate problematic attrition.