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Factorial Designs, Model Selection, and (Incorrect) Inference in Randomized Experiments

Authors :
Karthik Muralidharan
Mauricio Romero
Kaspar Wüthrich
Source :
SSRN Electronic Journal.
Publication Year :
2020
Publisher :
Elsevier BV, 2020.

Abstract

Factorial designs are widely used to study multiple treatments in one experiment. While t-tests using a fully-saturated “long” model provide valid inferences, “short” model t-tests (that ignore interactions) yield higher power if interactions are zero, but incorrect inferences otherwise. Of 27 factorial experiments published in top-5 journals (2007–2017), 19 use the short model. After including interactions, over half of their results lose significance. Based on recent econometric advances, we show that power improvements over the long model are possible. We provide practical guidance for the design of new experiments and the analysis of completed experiments.

Details

ISSN :
15565068
Database :
OpenAIRE
Journal :
SSRN Electronic Journal
Accession number :
edsair.doi.dedup.....ee6dd34cd02fe5a117325efff3997ff0
Full Text :
https://doi.org/10.2139/ssrn.3551804