An Applied Researcher’s Guide to Estimating Effects From Multisite Individually Randomized Trials: Estimands, Estimators, and Estimates
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Miratrix, Luke, Michael Weiss, and Brit Henderson. 2020. "An Applied Researcher’s Guide to Estimating Effects From Multisite Individually Randomized Trials: Estimands, Estimators, and Estimates." Journal of Research on Educational Effectiveness, forthcoming.Abstract
Researchers face many choices when conducting large-scale multisite individually randomized control trials. One of the most common quantities of interest in multisite RCTs is the overall average effect. Even this quantity is non-trivial to define and estimate. The researcher can target the average effect across individuals or sites. Furthermore, the researcher can target the effect for the experimental sample or a larger population. If treatment effects vary across sites, these estimands can differ. Once an estimand is selected, an estimator must be chosen. Standard estimators, such as fixed-effects regression, can be biased. We describe 15 estimators, consider which estimands they are appropriate for, and discuss their properties in the face of cross-site effect heterogeneity. Using data from 12 large multisite RCTs, we estimate the effect (and standard error) using each estimator and compare the results. We assess the extent that these decisions matter in practice and provide guidance for applied researchers.Terms of Use
This article is made available under the terms and conditions applicable to Open Access Policy Articles, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#OAPCitable link to this page
https://nrs.harvard.edu/URN-3:HUL.INSTREPOS:37366188
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