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.
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.
Authors: Annette M O'Connor; Brent Auvermann; Danelle Bickett-Weddle; Steve Kirkhorn; Jan M Sargeant; Alejandro Ramirez; Susanna G Von Essen Journal: PLoS One Date: 2010-03-10 Impact factor: 3.240