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      What is replication?

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      PLoS Biology
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          Abstract

          Credibility of scientific claims is established with evidence for their replicability using new data. According to common understanding, replication is repeating a study’s procedure and observing whether the prior finding recurs. This definition is intuitive, easy to apply, and incorrect. We propose that replication is a study for which any outcome would be considered diagnostic evidence about a claim from prior research. This definition reduces emphasis on operational characteristics of the study and increases emphasis on the interpretation of possible outcomes. The purpose of replication is to advance theory by confronting existing understanding with new evidence. Ironically, the value of replication may be strongest when existing understanding is weakest. Successful replication provides evidence of generalizability across the conditions that inevitably differ from the original study; Unsuccessful replication indicates that the reliability of the finding may be more constrained than recognized previously. Defining replication as a confrontation of current theoretical expectations clarifies its important, exciting, and generative role in scientific progress.

          Abstract

          What is replication? This Perspective article proposes that the answer shifts the conception of replication from a boring, uncreative, housekeeping activity to an exciting, generative, vital contributor to research progress.

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          Evaluating the replicability of social science experiments in Nature and Science between 2010 and 2015

          Being able to replicate scientific findings is crucial for scientific progress1-15. We replicate 21 systematically selected experimental studies in the social sciences published in Nature and Science between 2010 and 201516-36. The replications follow analysis plans reviewed by the original authors and pre-registered prior to the replications. The replications are high powered, with sample sizes on average about five times higher than in the original studies. We find a significant effect in the same direction as the original study for 13 (62%) studies, and the effect size of the replications is on average about 50% of the original effect size. Replicability varies between 12 (57%) and 14 (67%) studies for complementary replicability indicators. Consistent with these results, the estimated true-positive rate is 67% in a Bayesian analysis. The relative effect size of true positives is estimated to be 71%, suggesting that both false positives and inflated effect sizes of true positives contribute to imperfect reproducibility. Furthermore, we find that peer beliefs of replicability are strongly related to replicability, suggesting that the research community could predict which results would replicate and that failures to replicate were not the result of chance alone.
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            No Support for Historical Candidate Gene or Candidate Gene-by-Interaction Hypotheses for Major Depression Across Multiple Large Samples

            Interest in candidate gene and candidate gene-by-environment interaction hypotheses regarding major depressive disorder remains strong despite controversy surrounding the validity of previous findings. In response to this controversy, the present investigation empirically identified eighteen candidate genes for depression studied ten or more times and examined evidence for their relevance to depression phenotypes. Utilizing data from large population-based and case-control samples ( n ranging from 62,138 to 443,264 across subsamples), we conducted a series of preregistered analyses examining polymorphism main effects, polymorphism × environmental moderator interactions, and gene-level effects across a number of operational definitions of depression (e.g., lifetime diagnosis, current severity, episode recurrence) and environmental moderators (e.g., sexual or physical abuse during childhood, socioeconomic adversity). There was no clear evidence for any candidate gene polymorphism associations with depression phenotypes or any polymorphism × environmental moderator effects. As a set, depression candidate genes were no more associated with depression phenotypes than noncandidate genes. We demonstrate that phenotypic measurement error is unlikely to account for these null findings. Our results do not support previous depression candidate gene findings, wherein large genetic effects are frequently reported in samples orders of magnitude smaller than those examined here. Instead, our results suggest that early hypotheses about depression candidate genes were incorrect and that the large number of associations reported in the depression candidate gene literature are likely to be false positives.
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              A problem in theory

              The replication crisis facing the psychological sciences is widely regarded as rooted in methodological or statistical shortcomings. We argue that a large part of the problem is the lack of a cumulative theoretical framework or frameworks. Without an overarching theoretical framework that generates hypotheses across diverse domains, empirical programs spawn and grow from personal intuitions and culturally biased folk theories. By providing ways to develop clear predictions, including through the use of formal modelling, theoretical frameworks set expectations that determine whether a new finding is confirmatory, nicely integrating with existing lines of research, or surprising, and therefore requiring further replication and scrutiny. Such frameworks also prioritize certain research foci, motivate the use diverse empirical approaches and, often, provide a natural means to integrate across the sciences. Thus, overarching theoretical frameworks pave the way toward a more general theory of human behaviour. We illustrate one such a theoretical framework: dual inheritance theory.
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                Author and article information

                Journal
                PLoS Biol
                PLoS Biol
                plos
                plosbiol
                PLoS Biology
                Public Library of Science (San Francisco, CA USA )
                1544-9173
                1545-7885
                27 March 2020
                March 2020
                27 March 2020
                : 18
                : 3
                : e3000691
                Affiliations
                [1 ] Center for Open Science, Charlottesville, Virginia, United States of America
                [2 ] University of Virginia, Charlottesville, Virginia, United States of America
                Author notes

                We have read the journal’s policy and the authors of this manuscript have the following competing interests: BAN and TME are employees of the Center for Open Science, a nonprofit technology and culture change organization with a mission to increase openness, integrity, and reproducibility of research.

                Author information
                http://orcid.org/0000-0001-6797-5476
                http://orcid.org/0000-0002-4959-5143
                Article
                PBIOLOGY-D-20-00409
                10.1371/journal.pbio.3000691
                7100931
                32218571
                480be0c7-c5ca-496a-98ab-34c874a9cb95
                © 2020 Nosek, Errington

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Page count
                Figures: 2, Tables: 0, Pages: 8
                Funding
                This work was supported by grants from Arnold Ventures, John Templeton Foundation, Templeton World Charity Foundation, and Templeton Religion Trust. The funders had no role in the preparation of the manuscript or the decision to publish.
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