Logistic regression is a popular statistical method in studying the effects of covariates on binary outcomes. It has been widely used in both clinical trials and observational studies. However, the results from the univariate regression and from the multiple logistic regression tend to be conflicting. A covariate may show very strong effect on the outcome in the multiple regression but not in the univariate regression, and vice versa. These facts have not been well appreciated in biomedical research. Misuse of logistic regression is very prevalent in medical publications. In this paper, we study the inconsistency between the univariate and multiple logistic regressions and give advice in the model section in multiple logistic regression analysis.
逻辑回归是研究协变量对二元结果影响的一 种常用的统计方法。它已被广泛应用于临床试验和 观察性研究。然而，单因素回归得到的结果和多元 逻辑回归得到的结果往往是相互矛盾的。在多元回 归中可能对结果会显示出非常强烈的影响的一个协 变量在单因素回归中可能不会，反之亦然。这些事 实在生物医学研究中并没有引起足够的重视。误用 逻辑回归在医学出版物中非常普遍。在本文中，我 们研究了单因素和多因素逻辑回归分析的不一致性， 并在多元逻辑回归分析的模型部分中给出建议。.
Keywords: Conditional expectation; logistic regression; model selection.