Over the last few decades, social scientists have developed and applied a host of statistical methods to make valid causal inferences, known as the credibility revolution. This trend has primarily focused on internal validity — researchers aim to unbiasedly estimate causal effects within a study. However, one of the most important long-standing methodological debates is about external validity — how scientists can generalize causal findings beyond a specific study. This question of external validity has a long history in the social sciences, going...

When running multi-arm trials, experimenters may wish to both learn and evaluate data-driven policies; for example, learning which version of treatment is most effective and evaluating the effect of that treatment in comparison to a control condition. Response adaptive algorithms, which dynamically update treatment assignment mechanisms based on observed response, facilitate experimental designs where the most data is collected about the most effective interventions, and can improve policy learning over conventional randomized trials. I discuss design decisions when running adaptive...