Literature DB >> 35922130

Questionable Research Practices, Low Statistical Power, and Other Obstacles to Replicability: Why Preclinical Neuroscience Research Would Benefit from Registered Reports.

Randall J Ellis1.   

Abstract

Replicability, the degree to which a previous scientific finding can be repeated in a distinct set of data, has been considered an integral component of institutionalized scientific practice since its inception several hundred years ago. In the past decade, large-scale replication studies have demonstrated that replicability is far from favorable, across multiple scientific fields. Here, I evaluate this literature and describe contributing factors including the prevalence of questionable research practices (QRPs), misunderstanding of p-values, and low statistical power. I subsequently discuss how these issues manifest specifically in preclinical neuroscience research. I conclude that these problems are multifaceted and difficult to solve, relying on the actions of early and late career researchers, funding sources, academic publishers, and others. I assert that any viable solution to the problem of substandard replicability must include changing academic incentives, with adoption of registered reports being the most immediately impactful and pragmatic strategy. For animal research in particular, comprehensive reporting guidelines that document potential sources of sensitivity for experimental outcomes is an essential addition.
Copyright © 2022 Ellis.

Entities:  

Keywords:  metascience; questionable research practices; registered reports; replicability; reproducibility; statistical power

Mesh:

Year:  2022        PMID: 35922130      PMCID: PMC9351632          DOI: 10.1523/ENEURO.0017-22.2022

Source DB:  PubMed          Journal:  eNeuro        ISSN: 2373-2822


  116 in total

Review 1.  A dirty dozen: twelve p-value misconceptions.

Authors:  Steven Goodman
Journal:  Semin Hematol       Date:  2008-07       Impact factor: 3.851

2.  Systematic reviews and meta-analyses of preclinical studies: publication bias in laboratory animal experiments.

Authors:  D A Korevaar; L Hooft; G ter Riet
Journal:  Lab Anim       Date:  2011-07-07       Impact factor: 2.471

3.  Scientists rise up against statistical significance.

Authors:  Valentin Amrhein; Sander Greenland; Blake McShane
Journal:  Nature       Date:  2019-03       Impact factor: 49.962

4.  Making the hard problem of consciousness easier.

Authors:  Lucia Melloni; Liad Mudrik; Michael Pitts; Christof Koch
Journal:  Science       Date:  2021-05-28       Impact factor: 47.728

5.  Striatal action-value neurons reconsidered.

Authors:  Lotem Elber-Dorozko; Yonatan Loewenstein
Journal:  Elife       Date:  2018-05-31       Impact factor: 8.140

6.  Stability of inbred mouse strain differences in behavior and brain size between laboratories and across decades.

Authors:  Douglas Wahlsten; Alexander Bachmanov; Deborah A Finn; John C Crabbe
Journal:  Proc Natl Acad Sci U S A       Date:  2006-10-19       Impact factor: 11.205

7.  The Practical Alternative to the p Value Is the Correctly Used p Value.

Authors:  Daniël Lakens
Journal:  Perspect Psychol Sci       Date:  2021-02-09

8.  Distinguishing between exploratory and confirmatory preclinical research will improve translation.

Authors:  Jonathan Kimmelman; Jeffrey S Mogil; Ulrich Dirnagl
Journal:  PLoS Biol       Date:  2014-05-20       Impact factor: 8.029

9.  PSYCHOLOGY. Estimating the reproducibility of psychological science.

Authors: 
Journal:  Science       Date:  2015-08-28       Impact factor: 47.728

Review 10.  A checklist is associated with increased quality of reporting preclinical biomedical research: A systematic review.

Authors:  SeungHye Han; Tolani F Olonisakin; John P Pribis; Jill Zupetic; Joo Heung Yoon; Kyle M Holleran; Kwonho Jeong; Nader Shaikh; Doris M Rubio; Janet S Lee
Journal:  PLoS One       Date:  2017-09-13       Impact factor: 3.240

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