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- Brief communication Use of a SAS program for conditional maximum likelihood estimate in linear logistic model to fit pair matched data
- Keun Young Yoo
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Epidemiol Health 1990;12(1):93-99
DOI: https://doi.org/
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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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