| Literature DB >> 29531092 |
Beth Baribault1, Chris Donkin2, Daniel R Little3, Jennifer S Trueblood4, Zita Oravecz5, Don van Ravenzwaaij6, Corey N White7, Paul De Boeck8, Joachim Vandekerckhove9.
Abstract
We describe and demonstrate an empirical strategy useful for discovering and replicating empirical effects in psychological science. The method involves the design of a metastudy, in which many independent experimental variables-that may be moderators of an empirical effect-are indiscriminately randomized. Radical randomization yields rich datasets that can be used to test the robustness of an empirical claim to some of the vagaries and idiosyncrasies of experimental protocols and enhances the generalizability of these claims. The strategy is made feasible by advances in hierarchical Bayesian modeling that allow for the pooling of information across unlike experiments and designs and is proposed here as a gold standard for replication research and exploratory research. The practical feasibility of the strategy is demonstrated with a replication of a study on subliminal priming.Keywords: generalizability; many labs; metastudy; radical randomization; robustness
Mesh:
Year: 2018 PMID: 29531092 PMCID: PMC5856505 DOI: 10.1073/pnas.1708285114
Source DB: PubMed Journal: Proc Natl Acad Sci U S A ISSN: 0027-8424 Impact factor: 11.205