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Korean Journal of Epidemiology 1990;12(1): 93-99.
짝을 이룬 자료분석시 Linear Logistic Model을 이용한 Conditonal Maximum Likelihood Estimate 추정을 위해 사용가능한 SAS 프로그램 1예
유근영
Use of a SAS program for conditional maximum likelihood estimate in linear logistic model to fit pair matched data
Keun Young Yoo
Abstract
For the most valid estimation of matched odds ratios in the analysis of pair-matched data, the method of choice is the conditional maximum likelihood method. Many alternative methods have been suggested, but in most cases, they lead to biased estimations in comparison to the conditional maximum likelihood method. Despite developments in statistical software such as GLIM, EGRET, and EPILOG for conditional likelihood estimation, the applicability of the SAS program remains limited, although it is one of the most common and popular statistical computer programs. According to the modification suggested by Holdford, since the conditional probability of selection in pair-matched case-control studies approximately takes the form of a linear logistic model, a conditional likelihood estimate can be estimated using standard statistical software. In this study, the author introduces a simple SAS program using PROC LIFEREG, which is commonly used for survival function analysis, to estimate matched odds ratios.


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