Literature DB >> 27858205

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

Andreas Stang1,2, Markus Deckert3, Charles Poole4, Kenneth J Rothman5.   

Abstract

Since its introduction in the twentieth century, null hypothesis significance testing (NHST), a hybrid of significance testing (ST) advocated by Fisher and null hypothesis testing (NHT) developed by Neyman and Pearson, has become widely adopted but has also been a source of debate. The principal alternative to such testing is estimation with point estimates and confidence intervals (CI). Our aim was to estimate time trends in NHST, ST, NHT and CI reporting in abstracts of major medical and epidemiological journals. We reviewed 89,533 abstracts in five major medical journals and seven major epidemiological journals, 1975-2014, and estimated time trends in the proportions of abstracts containing statistical inference. In those abstracts, we estimated time trends in the proportions relying on NHST and its major variants, ST and NHT, and in the proportions reporting CIs without explicit use of NHST (CI-only approach). The CI-only approach rose monotonically during the study period in the abstracts of all journals. In Epidemiology abstracts, as a result of the journal's editorial policy, the CI-only approach has always been the most common approach. In the other 11 journals, the NHST approach started out more common, but by 2014, this disparity had narrowed, disappeared or reversed in 9 of them. The exceptions were JAMA, New England Journal of Medicine, and Lancet abstracts, where the predominance of the NHST approach prevailed over time. In 2014, the CI-only approach is as popular as the NHST approach in the abstracts of 4 of the epidemiology journals: the American Journal of Epidemiology (48%), the Annals of Epidemiology (55%), Epidemiology (79%) and the International Journal of Epidemiology (52%). The reporting of CIs without explicitly interpreting them as statistical tests is becoming more common in abstracts, particularly in epidemiology journals. Although NHST is becoming less popular in abstracts of most epidemiology journals studied and some widely read medical journals, it is still very common in the abstracts of other widely read medical journals, especially in the hybrid form of ST and NHT in which p values are reported numerically along with declarations of the presence or absence of statistical significance.

Entities:  

Keywords:  Confidence intervals; Statistics; Statistics and numerical data

Year:  2016        PMID: 27858205     DOI: 10.1007/s10654-016-0211-1

Source DB:  PubMed          Journal:  Eur J Epidemiol        ISSN: 0393-2990            Impact factor:   8.082


  17 in total

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4.  Confidence intervals rather than P values: estimation rather than hypothesis testing.

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Authors: 
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