Split-Sample Strategies for Avoiding False Discoveries

Michael Anderson and Jeremy Magruder

No 23544, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: Preanalysis plans (PAPs) have become an important tool for limiting false discoveries in field experiments. We evaluate the properties of an alternate approach which splits the data into two samples: An exploratory sample and a confirmation sample. When hypotheses are homogeneous, we describe an improved split-sample approach that achieves 90% of the rejections of the optimal PAP without requiring preregistration or constraints on specification search in the exploratory sample. When hypotheses are heterogeneous in priors or intrinsic interest, we find that a hybrid approach which prespecifies hypotheses with high weights and priors and uses a split-sample approach to test additional hypotheses can have power gains over any pure PAP. We assess this approach using the community-driven development (CDD) application from Casey et al. (2012) and find that the use of a hybrid split-sample approach would have generated qualitatively different conclusions.

JEL-codes: C12 C81 C9 C93 O1 (search for similar items in EconPapers)
Date: 2017-06
New Economics Papers: this item is included in nep-exp
Note: DEV LS PE
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Citations: View citations in EconPapers (17)

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