Literature DB >> 14738519

Editors can lead researchers to confidence intervals, but can't make them think: statistical reform lessons from medicine.

Fiona Fidler1, Neil Thomason, Geoff Cumming, Sue Finch, Joanna Leeman.   

Abstract

Since the mid-1980s, confidence intervals (CIs) have been standard in medical journals. We sought lessons for psychology from medicine's experience with statistical reform by investigating two attempts by Kenneth Rothman to change statistical practices. We examined 594 American Journal of Public Health (AJPH) articles published between 1982 and 2000 and 110 Epidemiology articles published in 1990 and 2000. Rothman's editorial instruction to report CIs and not p values was largely effective: In AJPH, sole reliance on p values dropped from 63% to 5%, and CI reporting rose from 10% to 54%; Epidemiology showed even stronger compliance. However, compliance was superficial: Very few authors referred to CIs when discussing results. The results of our survey support what other research has indicated: Editorial policy alone is not a sufficient mechanism for statistical reform. Achieving substantial, desirable change will require further guidance regarding use and interpretation of CIs and appropriate effect size measures. Necessary steps will include studying researchers' understanding of CIs, improving education, and developing empirically justified recommendations for improved statistical practice.

Mesh:

Year:  2004        PMID: 14738519     DOI: 10.1111/j.0963-7214.2004.01502008.x

Source DB:  PubMed          Journal:  Psychol Sci        ISSN: 0956-7976


  28 in total

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Authors:  Robert J Calin-Jageman; Geoff Cumming
Journal:  Am Stat       Date:  2019-03-20       Impact factor: 8.710

2.  Beyond statistical inference: a decision theory for science.

Authors:  Peter R Killeen
Journal:  Psychon Bull Rev       Date:  2006-08

3.  Thinking About Data, Research Methods, and Statistical Analyses: Commentary on Sijtsma's (2014) "Playing with Data".

Authors:  Irwin D Waldman; Scott O Lilienfeld
Journal:  Psychometrika       Date:  2016-03       Impact factor: 2.500

Review 4.  Statistical inference in abstracts of major medical and epidemiology journals 1975-2014: a systematic review.

Authors:  Andreas Stang; Markus Deckert; Charles Poole; Kenneth J Rothman
Journal:  Eur J Epidemiol       Date:  2016-11-17       Impact factor: 8.082

5.  Use of 95% confidence intervals in the reporting of between-group differences in randomized controlled trials: analysis of a representative sample of 200 physical therapy trials.

Authors:  Ana Paula Coelho Figueira Freire; Mark R Elkins; Ercy Mara Cipulo Ramos; Anne M Moseley
Journal:  Braz J Phys Ther       Date:  2018-10-16       Impact factor: 3.377

6.  Nearly significant if only….

Authors:  L A Harvey
Journal:  Spinal Cord       Date:  2018-11       Impact factor: 2.772

7.  After p Values: The New Statistics for Undergraduate Neuroscience Education.

Authors:  Robert J Calin-Jageman
Journal:  J Undergrad Neurosci Educ       Date:  2017-11-15

8.  A novel approach to quantify random error explicitly in epidemiological studies.

Authors:  Imre Janszky; Johan Håkon Bjørngaard; Pål Romundstad; Lars Vatten
Journal:  Eur J Epidemiol       Date:  2011-07-30       Impact factor: 8.082

9.  The null hypothesis significance test in health sciences research (1995-2006): statistical analysis and interpretation.

Authors:  Luis Carlos Silva-Ayçaguer; Patricio Suárez-Gil; Ana Fernández-Somoano
Journal:  BMC Med Res Methodol       Date:  2010-05-19       Impact factor: 4.615

10.  Multiple Imputation For Combined-Survey Estimation With Incomplete Regressors In One But Not Both Surveys.

Authors:  Michael S Rendall; Bonnie Ghosh-Dastidar; Margaret M Weden; Elizabeth H Baker; Zafar Nazarov
Journal:  Sociol Methods Res       Date:  2013-11-01
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