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Increasing Transparency Through a Multiverse Analysis.

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      Abstract

      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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      Affiliations
      [1] KU Leuven, University of Leuven.
      [2] Columbia University.
      [3] KU Leuven, University of Leuven wolf.vanpaemel@ppw.kuleuven.be.
      Journal
      Perspect Psychol Sci
      Perspectives on psychological science : a journal of the Association for Psychological Science
      1745-6924
      1745-6916
      Sep 2016
      : 11
      : 5
      27694465
      11/5/702
      10.1177/1745691616658637
      © The Author(s) 2016.
      Keywords:

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