Text mining describes the use of statistical and epidemiological methods in published medical research

Christopher Meaney, Rahim Moineddin, Teja Voruganti, Mary Ann O'Brien, Paul Krueger, Frank Sullivan

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

Objective: To describe trends in the use of statistical and epidemiological methods in the medical literature over the past 2 decades.

Study Design and Setting: We obtained all 1,028,786 articles from the PubMed Central Open-Access archive (retrieved May 9, 2015). We focused on 113,450 medical research articles. A Delphi panel identified 177 statistical/epidemiological methods pertinent to clinical researchers. We used a text-mining approach to determine if a specific statistical/epidemiological method was encountered in a given article. We report the proportion of articles using a specific method for the entire cross-sectional sample and also stratified into three blocks of time (1995-2005; 2006-2010; 2011-2015).

Results: Numeric descriptive statistics were commonplace (96.4% articles). Other frequently encountered methods groups included statistical inferential concepts (52.9% articles), epidemiological measures of association (53.5% articles) methods for diagnostic/classification accuracy (40.1% articles), hypothesis testing (28.8% articles), ANOVA (23.2% articles), and regression (22.6% articles). We observed relative percent increases in the use of: regression (103.0%), missing data methods (217.9%), survival analysis (147.6%), and correlated data analysis (192.2%).

Conclusions: This study identified commonly encountered and emergent methods used to investigate medical research problems. Clinical researchers must be aware of the methodological landscape in their field, as statistical/epidemiological methods underpin research claims.

Original languageEnglish
Pages (from-to)124-32
Number of pages9
JournalJournal of Clinical Epidemiology
Volume74
Early online date19 Dec 2015
DOIs
Publication statusPublished - Jun 2016

Keywords

  • Statistical methods
  • Epidemiological methods
  • Text mining
  • Bibliometrics
  • PubMed
  • Medical research

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