Campos-Filho N, Franco E L
Epidemiology and Biostatistics Unit, Ludwig Institute for Cancer Research, São Paulo, Brazil.
Am J Epidemiol. 1989 Feb;129(2):439-44. doi: 10.1093/oxfordjournals.aje.a115148.
A frequent procedure in matched case-control studies is to report results from the multivariate unmatched analyses if they do not differ substantially from the ones obtained after conditioning on the matching variables. Although conceptually simple, this rule requires that an extensive series of logistic regression models be evaluated by both the conditional and unconditional maximum likelihood methods. Most computer programs for logistic regression employ only one maximum likelihood method, which requires that the analyses be performed in separate steps. This paper describes a Pascal microcomputer (IBM PC) program that performs multiple logistic regression by both maximum likelihood estimation methods, which obviates the need for switching between programs to obtain relative risk estimates from both matched and unmatched analyses. The program calculates most standard statistics and allows factoring of categorical or continuous variables by two distinct methods of contrast. A built-in, descriptive statistics option allows the user to inspect the distribution of cases and controls across categories of any given variable.
在配对病例对照研究中,一个常见的做法是,如果多变量非配对分析的结果与在匹配变量条件下得到的结果没有实质性差异,就报告这些结果。虽然从概念上讲很简单,但这条规则要求通过条件和无条件最大似然法评估一系列广泛的逻辑回归模型。大多数用于逻辑回归的计算机程序只采用一种最大似然法,这就要求分析要分步骤进行。本文描述了一个用Pascal语言编写的微机(IBM个人计算机)程序,它通过两种最大似然估计方法进行多重逻辑回归,从而无需在不同程序之间切换就能从配对和非配对分析中获得相对风险估计值。该程序计算大多数标准统计量,并允许通过两种不同的对比方法对分类或连续变量进行因子分解。一个内置的描述性统计选项允许用户检查病例和对照在任何给定变量类别中的分布情况。