Literature DB >> 24205936

The life of p: "just significant" results are on the rise.

Nathan C Leggett1, Nicole A Thomas, Tobias Loetscher, Michael E R Nicholls.   

Abstract

Null hypothesis significance testing uses the seemingly arbitrary probability of .05 as a means of objectively determining whether a tested effect is reliable. Within recent psychological articles, research has found an overrepresentation of p values around this cut-off. The present study examined whether this overrepresentation is a product of recent pressure to publish or whether it has existed throughout psychological research. Articles published in 1965 and 2005 from two prominent psychology journals were examined. Like previous research, the frequency of p values at and just below .05 was greater than expected compared to p frequencies in other ranges. While this overrepresentation was found for values published in both 1965 and 2005, it was much greater in 2005. Additionally, p values close to but over .05 were more likely to be rounded down to, or incorrectly reported as, significant in 2005 than in 1965. Modern statistical software and an increased pressure to publish may explain this pattern. The problem may be alleviated by reduced reliance on p values and increased reporting of confidence intervals and effect sizes.

Mesh:

Year:  2013        PMID: 24205936     DOI: 10.1080/17470218.2013.863371

Source DB:  PubMed          Journal:  Q J Exp Psychol (Hove)        ISSN: 1747-0218            Impact factor:   2.143


  15 in total

1.  A surge of p-values between 0.041 and 0.049 in recent decades (but negative results are increasing rapidly too).

Authors:  Joost Cf de Winter; Dimitra Dodou
Journal:  PeerJ       Date:  2015-01-22       Impact factor: 2.984

2.  The Search for Significance: A Few Peculiarities in the Distribution of P Values in Experimental Psychology Literature.

Authors:  Michał Krawczyk
Journal:  PLoS One       Date:  2015-06-10       Impact factor: 3.240

3.  Conservative Tests under Satisficing Models of Publication Bias.

Authors:  Justin McCrary; Garret Christensen; Daniele Fanelli
Journal:  PLoS One       Date:  2016-02-22       Impact factor: 3.240

4.  Distributions of p-values smaller than .05 in psychology: what is going on?

Authors:  Chris H J Hartgerink; Robbie C M van Aert; Michèle B Nuijten; Jelte M Wicherts; Marcel A L M van Assen
Journal:  PeerJ       Date:  2016-04-11       Impact factor: 2.984

5.  Significance bias: an empirical evaluation of the oral health literature.

Authors:  Edwin Kagereki; Joseph Gakonyo; Hazel Simila
Journal:  BMC Oral Health       Date:  2016-05-05       Impact factor: 2.757

6.  On the challenges of drawing conclusions from p-values just below 0.05.

Authors:  Daniël Lakens
Journal:  PeerJ       Date:  2015-07-30       Impact factor: 2.984

7.  The extent and consequences of p-hacking in science.

Authors:  Megan L Head; Luke Holman; Rob Lanfear; Andrew T Kahn; Michael D Jennions
Journal:  PLoS Biol       Date:  2015-03-13       Impact factor: 8.029

8.  Outlier removal and the relation with reporting errors and quality of psychological research.

Authors:  Marjan Bakker; Jelte M Wicherts
Journal:  PLoS One       Date:  2014-07-29       Impact factor: 3.240

9.  Publication bias in psychology: a diagnosis based on the correlation between effect size and sample size.

Authors:  Anton Kühberger; Astrid Fritz; Thomas Scherndl
Journal:  PLoS One       Date:  2014-09-05       Impact factor: 3.240

10.  Statistical Reporting Errors and Collaboration on Statistical Analyses in Psychological Science.

Authors:  Coosje L S Veldkamp; Michèle B Nuijten; Linda Dominguez-Alvarez; Marcel A L M van Assen; Jelte M Wicherts
Journal:  PLoS One       Date:  2014-12-10       Impact factor: 3.240

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