Figueiras A, Domenech-Massons J M, Cadarso C
Department of Preventive Medicine and Public Health, University of Santiago, Spain.
Stat Med. 1998 Sep 30;17(18):2099-105. doi: 10.1002/(sici)1097-0258(19980930)17:18<2099::aid-sim905>3.0.co;2-6.
The main goal of regression analysis (multiple, logistic, Cox) is to assess the relationship of one or more exposure variables to a response variable, in the presence of confounding and interaction. The confidence interval for the regression coefficient of the exposure variable, obtained through the use of a computer statistical package, quantify these relationships for models without interaction. Relationships between variables that present interactions are represented by two or more terms, and the corresponding confidence intervals can be calculated 'manually' from the covariance matrix. This paper suggests an easy procedure for obtaining confidence intervals from any statistical package. This procedure is applicable for modifying variables which are continuous as well as categorical.
回归分析（多元回归、逻辑回归、Cox回归）的主要目标是在存在混杂和交互作用的情况下，评估一个或多个暴露变量与一个反应变量之间的关系。通过使用计算机统计软件包获得的暴露变量回归系数的置信区间，对无交互作用的模型量化这些关系。存在交互作用的变量之间的关系由两个或更多项表示，相应的置信区间可从协方差矩阵“手动”计算得出。本文提出了一种从任何统计软件包中获取置信区间的简便方法。该方法适用于连续变量和分类变量的修正。
