Bouyer J
INSERM U170: Unité de Recherches Epidémiologiques et Statistiques sur l'Environnement et la Santé, Villejuif.
Rev Epidemiol Sante Publique. 1991;39(1):79-87.
The logistic regression is used in epidemiology to study the relationships between a disease in two modalities (diseased or disease free) and risk factors Xi which may be qualitative or quantitative variables. According to this model, the probability of disease knowing Xi's values is written: [formula: see text]. The coefficients beta i satisfy to the equation: ORi = exp(beta i) where ORi is the odds-ratio linked to the variable Xi adjusted on the other variables of the model. The first part of this paper indicates the way to include in the model qualitative variables with more than two modalities, quantitative variables and interaction between variables. At least, the maximum likelihood method to estimate the parameters of the model is presented.
逻辑回归在流行病学中用于研究两种状态（患病或未患病）的疾病与可能为定性或定量变量的风险因素Xi之间的关系。根据该模型，已知Xi值时患病的概率可表示为：[公式：见原文]。系数βi满足方程：ORi = exp(βi)，其中ORi是与变量Xi相关的比值比，已根据模型中的其他变量进行了调整。本文的第一部分指出了将具有两种以上状态的定性变量、定量变量以及变量间的相互作用纳入模型的方法。最后，介绍了估计模型参数的最大似然法。
