Evaluation of logistic regression reporting in current obstetrics and gynecology literature.
OBJECTIVE
To evaluate the quality of logistic regression reporting in the obstetrics and gynecology literature.


METHODS
All original papers published in 2005 and 2006 in four leading obstetrics and gynecology journals were manually searched for the use of logistic regression. One hundred four articles that used logistic regression were randomly selected (13 from each journal and each year) and evaluated according to previously established criteria for reporting logistic regression analyses. Rates of compliance with these criteria were calculated separately for each journal and weighted according to the number of articles using logistic regression in each of the journals in the same period to obtain an overall estimate.


RESULTS
Logistic regression was used in 34.2% of all original research articles (724 of 2,234) in the four journals for the study period. Statistical significance of estimates was reported in 96% of examined articles. Criteria of variable selection for the logistic regression model were reported in 76% of articles, and coding of variables was described in 83%. Overfitting (models with too many variables for the number of outcome events) occurred in 57% of studies. The majority of examined articles insufficiently reported information for the remaining criteria-testing for interactions (18%), conformity to a linear gradient of continuous variables (9%), goodness of fit (3.6%), assessment of multi-collinearity (0.46%), and validation of the model (0%).


CONCLUSIONS
Logistic regression has become a standard statistical method in obstetrics and gynecology literature. Although some standards are mostly fulfilled, there is still considerable room for improvement.


METHODS
III.
Mikolajczyk
Rafael T
RT
Epidemiology Branch, the National Institute of Child Health and Human Development, the National Institutes of Health, Bethesda, Maryland 20892-7510, USA. mikorafa@mail.nih.gov
DiSilvestro
Alexis
A
DiSilvesto
Alexis
A
Zhang
Jun
J
D003627:Data Interpretation, Statistical; D005260:Female; D006176:Gynecology; D006801:Humans; D016015:Logistic Models; D009774:Obstetrics; D010506:Periodicals as Topic; D011643:Publishing / Q000706:statistics & numerical data; D013223:Statistics as Topic