|Time:||12:30 pm on Wednesday, April 18, 2012|
Researchers in political science generally enjoy substantial latitude in selecting measures and models for hypothesis testing. Coupled with publication and related biases, this latitude raises the concern that researchers may intentionally or unintentionally select models that yield positive findings, leading to an unreliable body of published research. To combat this problem of "data fishing" in medical studies, leading journals now require preregistration of designs that emphasize the prior identification of dependent and independent variables. However, we demonstrate here that even with this level of advanced specification, the scope for fishing is considerable when there is latitude over selection of covariates, subgroups, and other elements of an analysis plan. These concerns could be addressed through the use of a form of "comprehensive registration." We experiment with such an approach in the context of an ongoing field experiment for which we drafted a complete "mock report" of findings using fake data on treatment assignment. We describe the advantages and disadvantages of this form of comprehensive registration and propose that a comprehensive but non-binding approach be adopted as a first step in registration in political science. Likely eff ects of a comprehensive but non-binding registration are discussed, the principle advantage being communication rather than commitment, in particular that it generates a clear distinction between exploratory analyses and genuine tests.
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