A review of two journals found that articles using multivariable logistic regression frequently did not report commonly recommended assumptions

  • Kenneth J. Ottenbacher
  • , Heather R. Ottenbacher
  • , Leigh Tooth
  • , Glenn V. Ostir

Research output: Contribution to journalArticlepeer-review

108 Scopus citations

Abstract

To examine if commonly recommended assumptions for multivariable logistic regression are addressed in two major epidemiological journals. Ninety-nine articles from the Journal of Clinical Epidemiology and the American Journal of Epidemiology were surveyed for 10 criteria: six dealing with computation and four with reporting multivariable logistic regression results. Three of the 10 criteria were addressed in 50% or more of the articles. Statistical significance testing or confidence intervals were reported in all articles. Methods for selecting independent variables were described in 82%, and specific procedures used to generate the models were discussed in 65%. Fewer than 50% of the articles indicated if interactions were tested or met the recommended events per independent variable ratio of 10:1. Fewer than 20% of the articles described conformity to a linear gradient, examined collinearity, reported information on validation procedures, goodness-of-fit, discrimination statistics, or provided complete information on variable coding. There was no significant difference (P >. 05) in the proportion of articles meeting the criteria across the two journals. Articles reviewed frequently did not report commonly recommended assumptions for using multivariable logistic regression.

Original languageEnglish (US)
Pages (from-to)1147-1152
Number of pages6
JournalJournal of Clinical Epidemiology
Volume57
Issue number11
DOIs
StatePublished - Nov 2004

Keywords

  • Outcomes research
  • Research design
  • Statistical tests

ASJC Scopus subject areas

  • Epidemiology

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