# Naoki Egami (Workshop in Applied Statistics) #### calendar\_today Date and Time **April 12, 2023** 12:00PM - 01:30PM EDT #### pin\_drop Location **CGIS Knafel Building, room K354 or Online via Zoom** ### **Today's Speaker** Naoki Egami (Columbia), "Empirical Strategies Toward External Validity: Framework and External Robustness" ### **Abstract** 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 back to at least the 1960s, and it has recently become even more essential, given that huge opportunities and challenges of accumulating causal knowledge have become evident. In this talk, I will discuss a set of empirical strategies to improve external validity in practice. I briefly introduce a formal framework of external validity (Egami and Hartman, 2022; APSR) that synthesizes diverse external validity concerns. Then, I will propose a new simple approach to quantify the robustness of experimental results to external validity bias (Devaux and Egami, 2022; Egami and Rothenhäusler, 2023+). In particular, I introduce a measure of external robustness, which ranges from 0 to 1 and represents how well causal effects estimated in one’s study can be generalized to other populations and contexts. Researchers can estimate this quantity using only experimental data (i.e., no additional data collection), and users can also account for unmeasured confounders. I discuss a debiased estimator, which is consistent and asymptotically normal under mild rate conditions that allow for the use of machine learning estimators. Finally, I provide default benchmarks and discuss practical guides about how to report external robustness in practice using the R package “exr” (). Papers: 1. [https://naokiegami.com/paper/external\_full.pdf](https://naokiegami.com/paper/external_full.pdf) 2. [https://naokiegami.com/paper/external\_robust.pdf](https://naokiegami.com/paper/external_robust.pdf) *The Applied Statistics Workshop (Gov 3009) meets all academic year, Wednesdays, 12pm-1:30pm, in CGIS K354. This workshop is a forum for advanced graduate students, faculty, and visiting scholars to present and discuss methodological or empirical work in progress in an interdisciplinary setting. The workshop features a tour of Harvard's statistical innovations and applications with weekly stops in different fields and disciplines and includes occasional presentations by invited speakers.* *More information is available at the Gov 3009 website: * *All interested Harvard affiliates are invited to attend.* See also:- [ Workshops, Seminars & Classes ](/event-type/workshops-seminars-classes) Share on:- [ Facebook ](#) - [ Twitter ](#) - [ Linkedin ](#) Save: [ Add to calendar calendar\_today ](https://www.iq.harvard.edu/node/1663886/event-feed.ics) Copy link link