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The role of meta-analysis and preregistration in assessing the evidence for cleansing effects

Published online by Cambridge University Press:  18 February 2021

Robert M. Ross Open the ORCID record for Robert M. Ross [Opens in a new window] ,
Robbie C. M. van Aert Open the ORCID record for Robbie C. M. van Aert [Opens in a new window] ,
Olmo R. van den Akker Open the ORCID record for Olmo R. van den Akker [Opens in a new window]  and
Michiel van Elk
Robert M. Ross
Affiliation:
Department of Philosophy, Macquarie University, Macquarie Park, NSW 2109, [email protected]://researchers.mq.edu.au/en/persons/robert-ross
Robbie C. M. van Aert
Affiliation:
Department of Methodology & Statistics, 5037 AB Tilburg University, Tilburg, The [email protected]://www.robbievanaert.com/; [email protected]://www.ovdakker.com
Olmo R. van den Akker
Affiliation:
Department of Methodology & Statistics, 5037 AB Tilburg University, Tilburg, The [email protected]://www.robbievanaert.com/; [email protected]://www.ovdakker.com
Michiel van Elk
Affiliation:
Department of Psychology, University of Leiden, 2311 EZLeiden, The Netherlands. [email protected]://www.uva.nl/profiel/e/l/m.vanelk/m.vanelk.html
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Abstract

Lee and Schwarz interpret meta-analytic research and replication studies as providing evidence for the robustness of cleansing effects. We argue that the currently available evidence is unconvincing because (a) publication bias and the opportunistic use of researcher degrees of freedom appear to have inflated meta-analytic effect size estimates, and (b) preregistered replications failed to find any evidence of cleansing effects.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 44 , 2021 , e19
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Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

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References

Bakker, M., Veldkamp, C. L. S., van Assen, M. A. L. M., Crompvoets, E. A. V., Ong, H. H., Nosek, B. A., … Wicherts, J. M. (2020). Ensuring the quality and specificity of preregistrations. https://doi.org/10.31234/osf.io/cdgyh.CrossRefGoogle Scholar
Camerer, C. F., Dreber, A., Holzmeister, F., Ho, T. H., Huber, J., Johannesson, M., … Wu, H. (2018). Evaluating the replicability of social science experiments in nature and science between 2010 and 2015. Nature Human Behavior, 2(9), 637–644. doi: 10.1038/s41562-018-0399-z.CrossRefGoogle ScholarPubMed
Carter, E. C., Schonbrodt, F. D., Gervais, W. M., & Hilgard, J. (2019). Correcting for bias in psychology: A comparison of meta-analytic methods. Advances in Methods and Practices in Psychological Science, 2(2), 115–144. https://doi.org/10.1177/2515245919847196.CrossRefGoogle Scholar
Claesen, A., Gomes, S., Tuerlinckx, F., & Vanpaemel, W. (2020). Preregistration: Comparing dream to reality. https://doi.org/10.31234/osf.io/d8wex.CrossRefGoogle Scholar
Du, H., Liu, F., & Wang, L. (2017). A Bayesian “fill-in” method for correcting for publication bias in meta-analysis. Psychological Methods, 22(4), 799–817. doi: 10.1037/met0000164.CrossRefGoogle ScholarPubMed
Iyengar, S., & Greenhouse, J. B. (1988). Selection models and the file drawer problem. Statistical Science, 3(1), 109–135.CrossRefGoogle Scholar
Johnson, D. J., Cheung, F., & Donnellan, M. B. (2014b). Does cleanliness influence moral judgments?: A direct replication of Schnall, Benton, and Harvey (2008). Social Psychology, 45(3), 209–215. https://doi.org/10.1027/1864-9335/a000186.CrossRefGoogle Scholar
Klein, R. A., Fasselman, F., Adams, B. G., Adamsn, R. B., Alper, S., Aveyard, M., … Nosek, B. A. (2018). Many Labs 2: Investigating variation in replicability across sample and setting. Advances in Methods and Practices in Psychological Science, 1(4), 443–490. https://doi.org/10.1177/2515245918810225.CrossRefGoogle Scholar
Kvarven, A., Stromland, E., & Johannesson, M. (2020). Comparing meta-analyses and preregistered multiple-laboratory replication projects. Nature Human Behaviour, 4, 423–434. doi: 10.1038/s41562-019-0787-z.CrossRefGoogle ScholarPubMed
Lakens, D. (2019). The value of preregistration for psychological science: A conceptual analysis. Japanese Psychological Review, 62(3), 221–230.Google Scholar
Lee, S. W. S., Chen, K., Ma, C., & Hoang, J. (2020a). Psychological antecedents and consequences of physical cleansing: A meta-analytic review [manuscript in preparation].Google Scholar
Lee, S. W. S., & Schwarz, N. (2010a). Washing away postdecisional dissonance. Science (New York, N.Y.), 328, 709. https://doi.org/10.1126/science.1186799.CrossRefGoogle Scholar
Lodder, P., Ong, H. H., Grasman, R. P. P. P., & Wicherts, J. M. (2019). A comprehensive meta-analysis of money priming. Journal of Experimental Psychology: General, 148(4), 688–712. doi: 10.1037/xge0000570.CrossRefGoogle ScholarPubMed
Nosek, B. A., Ebersole, C. R., DeHaven, A. C., & Mellor, D. T. (2018). The preregistration revolution. Proceedings of the National Academy of Sciences, 115(11), 2600–2606. doi: 10.1073/pnas.1708274114.CrossRefGoogle ScholarPubMed
Open Science Collaboration. (2015). Estimating the reproducibility of psychological science. Science (New York, N.Y.), 349(6251), aac4716. doi: 10.1126/science.aac4716.CrossRefGoogle Scholar
Peters, J. L., Sutton, A. J., Jones, D. R., Abrams, K. R., & Rushton, L. (2007). Performance of the trim and fill method in the presence of publication bias and between-study heterogeneity. Statistics in Medicine, 26(25), 4544–4562. doi: 10.1002/sim.2889.CrossRefGoogle ScholarPubMed
Schnall, S., Benton, J., & Harvey, S. (2008). With a clean conscience cleanliness reduces the severity of moral judgments. Psychological Science, 19(12), 1219–1222. doi: 10.1111/j.1467-9280.2008.02227.x.CrossRefGoogle ScholarPubMed
Simonsohn, U., Nelson, L. D., & Simmons, J. P. (2014a). p-Curve and effect size: Correcting for publication bias using only significant results. Perspectives on Psychological Science, 9(6), 666–681. doi: 10.1177/1745691614553988.CrossRefGoogle Scholar
Stanley, T. D., & Doucouliagos, C. H. (2014). Meta-regression approximations to reduce publication selection bias. Research Synthesis Methods, 5(1), 60–78. doi: 10.1002/jrsm.1095.CrossRefGoogle ScholarPubMed
Terrin, N., Schmid, C. H., Lau, J., & Olkin, I. (2003). Adjusting for publication bias in the presence of heterogeneity. Statistics in Medicine, 22(13), 2113–2126. doi: 10.1002/sim.1461.CrossRefGoogle ScholarPubMed
van Aert, R. C. M., & van Assen, M. A. L. M. (2020). Correcting for publication bias in a meta-analysis with the p-uniform* method. https://doi.org/10.31222/osf.io/zqjr9.CrossRefGoogle Scholar
van Elk, M., Matzke, D., Gronau, Q. F., Guana, M., Vandekerckhove, J., & Wagenmakers, E. J. (2015). Meta-analyses are no substitute for registered replications: A skeptical perspective on religious priming. Frontiers in Psychology, 6, 1–7. doi: 10.3389/fpsyg.2015.01365.CrossRefGoogle ScholarPubMed
Wicherts, J. M., Veldkamp, C. L. S., Augusteijn, H. E. M., Bakker, M., van Aert, R. C., & van Assen, M. A. (2016). Degrees of freedom in planning, running, analyzing, and reporting psychological studies: A checklist to avoid p-hacking. Frontiers in Psychology, 7, 1–12. doi: 10.3389/fpsyg.2016.01832.CrossRefGoogle ScholarPubMed
Zhong, C. B., & Liljenquist, K. (2006). Washing away your sins: Threatened morality and physical cleansing. Science (New York, N.Y.), 313(5792), 1451–1452. https://doi.org/10.1126/science.1130726.CrossRefGoogle ScholarPubMed