Wacholder S
Am J Epidemiol. 1986 Jan;123(1):174-84. doi: 10.1093/oxfordjournals.aje.a114212.
Although an estimate of the odds ratio adjusted for other covariates can be obtained by logistic regression, until now there has been no simple way to estimate other interesting parameters such as the risk ratio and risk difference multivariately for prospective binomial data. These parameters can be estimated in the generalized linear model framework by choosing different link functions or transformations of binomial or binary data. Macros for use with the program GLIM provide a simple method to compute parameters other than the odds ratio while adjusting for confounding factors. A data set presented previously is used as an example.
尽管可以通过逻辑回归获得针对其他协变量调整后的优势比估计值，但到目前为止，对于前瞻性二项数据，尚无简单方法来多变量估计其他有趣的参数，如风险比和风险差异。通过选择二项或二元数据的不同连接函数或变换，可以在广义线性模型框架中估计这些参数。与GLIM程序一起使用的宏提供了一种在调整混杂因素的同时计算除优势比之外的参数的简单方法。以前呈现的一个数据集用作示例。
