Literature DB >> 31413381

Before p < 0.05 to Beyond p < 0.05: Using History to Contextualize p-Values and Significance Testing.

Lee Kennedy-Shaffer1.   

Abstract

As statisticians and scientists consider a world beyond p < 0.05, it is important to not lose sight of how we got to this point. Although significance testing and p-values are often presented as prescriptive procedures, they came about through a process of refinement and extension to other disciplines. Ronald A. Fisher and his contemporaries formalized these methods in the early twentieth century and Fisher's 1925 Statistical Methods for Research Workers brought the techniques to experimentalists in a variety of disciplines. Understanding how these methods arose, spread, and were argued over since then illuminates how p < 0.05 came to be a standard for scientific inference, the advantage it offered at the time, and how it was interpreted. This historical perspective can inform the work of statisticians today by encouraging thoughtful consideration of how their work, including proposed alternatives to the p-value, will be perceived and used by scientists. And it can engage students more fully and encourage critical thinking rather than rote applications of formulae. Incorporating history enables students, practitioners, and statisticians to treat the discipline as an ongoing endeavor, crafted by fallible humans, and provides a deeper understanding of the subject and its consequences for science and society.

Entities:  

Keywords:  Education; Foundational Issues; Hypothesis Testing; Inference; Probability

Year:  2019        PMID: 31413381      PMCID: PMC6693672          DOI: 10.1080/00031305.2018.1537891

Source DB:  PubMed          Journal:  Am Stat        ISSN: 0003-1305            Impact factor:   8.710


  7 in total

1.  The fallacy of the null-hypothesis significance test.

Authors:  W W ROZEBOOM
Journal:  Psychol Bull       Date:  1960-09       Impact factor: 17.737

2.  Redefine statistical significance.

Authors:  Daniel J Benjamin; James O Berger; Magnus Johannesson; Brian A Nosek; E-J Wagenmakers; Richard Berk; Kenneth A Bollen; Björn Brembs; Lawrence Brown; Colin Camerer; David Cesarini; Christopher D Chambers; Merlise Clyde; Thomas D Cook; Paul De Boeck; Zoltan Dienes; Anna Dreber; Kenny Easwaran; Charles Efferson; Ernst Fehr; Fiona Fidler; Andy P Field; Malcolm Forster; Edward I George; Richard Gonzalez; Steven Goodman; Edwin Green; Donald P Green; Anthony G Greenwald; Jarrod D Hadfield; Larry V Hedges; Leonhard Held; Teck Hua Ho; Herbert Hoijtink; Daniel J Hruschka; Kosuke Imai; Guido Imbens; John P A Ioannidis; Minjeong Jeon; James Holland Jones; Michael Kirchler; David Laibson; John List; Roderick Little; Arthur Lupia; Edouard Machery; Scott E Maxwell; Michael McCarthy; Don A Moore; Stephen L Morgan; Marcus Munafó; Shinichi Nakagawa; Brendan Nyhan; Timothy H Parker; Luis Pericchi; Marco Perugini; Jeff Rouder; Judith Rousseau; Victoria Savalei; Felix D Schönbrodt; Thomas Sellke; Betsy Sinclair; Dustin Tingley; Trisha Van Zandt; Simine Vazire; Duncan J Watts; Christopher Winship; Robert L Wolpert; Yu Xie; Cristobal Young; Jonathan Zinman; Valen E Johnson
Journal:  Nat Hum Behav       Date:  2018-01

3.  Models, inference, and strategy.

Authors:  J G Skellam
Journal:  Biometrics       Date:  1969-09       Impact factor: 2.571

4.  The test of significance in psychological research.

Authors:  D Bakan
Journal:  Psychol Bull       Date:  1966-12       Impact factor: 17.737

5.  When the Alpha is the Omega: P-Values, "Substantial Evidence," and the 0.05 Standard at FDA.

Authors:  Lee Kennedy-Shaffer
Journal:  Food Drug Law J       Date:  2017       Impact factor: 0.619

6.  Why most published research findings are false.

Authors:  John P A Ioannidis
Journal:  PLoS Med       Date:  2005-08-30       Impact factor: 11.613

7.  Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations.

Authors:  Sander Greenland; Stephen J Senn; Kenneth J Rothman; John B Carlin; Charles Poole; Steven N Goodman; Douglas G Altman
Journal:  Eur J Epidemiol       Date:  2016-05-21       Impact factor: 8.082

  7 in total
  8 in total

1.  Health Status and Chronic Disease Burden of the Homeless Population: An Analysis of Two Decades of Multi-Institutional Electronic Medical Records.

Authors:  Wyatt P Bensken; Nikolas I Krieger; Kristen A Berg; Douglas Einstadter; Jarrod E Dalton; Adam T Perzynski
Journal:  J Health Care Poor Underserved       Date:  2021

2.  So, what about P?

Authors:  Vladimir Trkulja; Pero Hrabač
Journal:  Croat Med J       Date:  2019-10-31       Impact factor: 1.351

3.  bmd: an R package for benchmark dose estimation.

Authors:  Signe M Jensen; Felix M Kluxen; Jens C Streibig; Nina Cedergreen; Christian Ritz
Journal:  PeerJ       Date:  2020-12-17       Impact factor: 2.984

4.  Baseline Arterial CO2 Pressure Regulates Acute Intermittent Hypoxia-Induced Phrenic Long-Term Facilitation in Rats.

Authors:  Raphael R Perim; Mohamed El-Chami; Elisa J Gonzalez-Rothi; Gordon S Mitchell
Journal:  Front Physiol       Date:  2021-02-24       Impact factor: 4.566

Review 5.  A Review of Bayesian Hypothesis Testing and Its Practical Implementations.

Authors:  Zhengxiao Wei; Aijun Yang; Leno Rocha; Michelle F Miranda; Farouk S Nathoo
Journal:  Entropy (Basel)       Date:  2022-01-21       Impact factor: 2.524

6.  The Fragility Index for Assessing the Robustness of the Statistically Significant Results of Experimental Clinical Studies.

Authors:  Adrienne K Ho
Journal:  J Gen Intern Med       Date:  2021-08-06       Impact factor: 5.128

Review 7.  Basic Introduction to Statistics in Medicine, Part 1: Describing Data.

Authors:  Wyatt P Bensken; Fredric M Pieracci; Vanessa P Ho
Journal:  Surg Infect (Larchmt)       Date:  2021-08       Impact factor: 1.853

8.  Basic Introduction to Statistics in Medicine, Part 2: Comparing Data.

Authors:  Wyatt P Bensken; Vanessa P Ho; Fredric M Pieracci
Journal:  Surg Infect (Larchmt)       Date:  2021-08       Impact factor: 1.853

  8 in total

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