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      Hormonal influences on women's extra-pair sexual interests: The moderating impact of partner attractiveness

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      Evolution and Human Behavior
      Elsevier BV

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          Scientists rise up against statistical significance

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            Balancing Type I error and power in linear mixed models

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              Increasing Transparency Through a Multiverse Analysis.

              Empirical research inevitably includes constructing a data set by processing raw data into a form ready for statistical analysis. Data processing often involves choices among several reasonable options for excluding, transforming, and coding data. We suggest that instead of performing only one analysis, researchers could perform a multiverse analysis, which involves performing all analyses across the whole set of alternatively processed data sets corresponding to a large set of reasonable scenarios. Using an example focusing on the effect of fertility on religiosity and political attitudes, we show that analyzing a single data set can be misleading and propose a multiverse analysis as an alternative practice. A multiverse analysis offers an idea of how much the conclusions change because of arbitrary choices in data construction and gives pointers as to which choices are most consequential in the fragility of the result.
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                Author and article information

                Journal
                Evolution and Human Behavior
                Evolution and Human Behavior
                Elsevier BV
                10905138
                September 2022
                September 2022
                : 43
                : 5
                : 442-454
                Article
                10.1016/j.evolhumbehav.2022.08.001
                3aa38793-ae2b-44c7-914a-8d0c8bf19986
                © 2022

                https://www.elsevier.com/tdm/userlicense/1.0/

                http://www.elsevier.com/open-access/userlicense/1.0/

                https://doi.org/10.15223/policy-017

                https://doi.org/10.15223/policy-037

                https://doi.org/10.15223/policy-012

                https://doi.org/10.15223/policy-029

                https://doi.org/10.15223/policy-004

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