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

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.