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

J Clin Epidemiol. 2004 Nov;57(11):1147-52. doi: 10.1016/j.jclinepi.2003.05.003.

Abstract

Background and objective: To examine if commonly recommended assumptions for multivariable logistic regression are addressed in two major epidemiological journals.

Methods: 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.

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.

Conclusion: Articles reviewed frequently did not report commonly recommended assumptions for using multivariable logistic regression.

Publication types

  • Research Support, U.S. Gov't, P.H.S.
  • Review

MeSH terms

  • Epidemiologic Methods*
  • Humans
  • Logistic Models
  • Multivariate Analysis
  • Periodicals as Topic
  • Reproducibility of Results