Literature DB >> 33180514

The reproducibility of statistical results in psychological research: An investigation using unpublished raw data.

Richard Artner1, Thomas Verliefde1, Sara Steegen1, Sara Gomes1, Frits Traets1, Francis Tuerlinckx1, Wolf Vanpaemel1.   

Abstract

We investigated the reproducibility of the major statistical conclusions drawn in 46 articles published in 2012 in three APA journals. After having identified 232 key statistical claims, we tried to reproduce, for each claim, the test statistic, its degrees of freedom, and the corresponding p value, starting from the raw data that were provided by the authors and closely following the Method section in the article. Out of the 232 claims, we were able to successfully reproduce 163 (70%), 18 of which only by deviating from the article's analytical description. Thirteen (7%) of the 185 claims deemed significant by the authors are no longer so. The reproduction successes were often the result of cumbersome and time-consuming trial-and-error work, suggesting that APA style reporting in conjunction with raw data makes numerical verification at least hard, if not impossible. This article discusses the types of mistakes we could identify and the tediousness of our reproduction efforts in the light of a newly developed taxonomy for reproducibility. We then link our findings with other findings of empirical research on this topic, give practical recommendations on how to achieve reproducibility, and discuss the challenges of large-scale reproducibility checks as well as promising ideas that could considerably increase the reproducibility of psychological research. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

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Year:  2020        PMID: 33180514     DOI: 10.1037/met0000365

Source DB:  PubMed          Journal:  Psychol Methods        ISSN: 1082-989X


  2 in total

1.  The influence of journal submission guidelines on authors' reporting of statistics and use of open research practices: Five years later.

Authors:  David Giofrè; Ingrid Boedker; Geoff Cumming; Carlotta Rivella; Patrizio Tressoldi
Journal:  Behav Res Methods       Date:  2022-10-17

2.  A computational reproducibility study of PLOS ONE articles featuring longitudinal data analyses.

Authors:  Heidi Seibold; Severin Czerny; Siona Decke; Roman Dieterle; Thomas Eder; Steffen Fohr; Nico Hahn; Rabea Hartmann; Christoph Heindl; Philipp Kopper; Dario Lepke; Verena Loidl; Maximilian Mandl; Sarah Musiol; Jessica Peter; Alexander Piehler; Elio Rojas; Stefanie Schmid; Hannah Schmidt; Melissa Schmoll; Lennart Schneider; Xiao-Yin To; Viet Tran; Antje Völker; Moritz Wagner; Joshua Wagner; Maria Waize; Hannah Wecker; Rui Yang; Simone Zellner; Malte Nalenz
Journal:  PLoS One       Date:  2021-06-21       Impact factor: 3.240

  2 in total

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