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American Journal of Epidemiology Vol. 130, No. 6: 1247-1253
Copyright © 1989 by The Johns Hopkins University School of Hygiene and Public Health

research-article

LOG-LINEAR MODELS FOR THE ANALYSIS OF MATCHED COHORT STUDIES

THEODORE R. HOLFORD1,, MICHAEL B. BRACKEN1 and BRENDA ESKENAZ2

1Department of Epidemiology and Public Health, Yale University School of Medicine P.O. Box 3333, New Haven, CT 06510
2Maternal and Child Health and Epidemiology, School of Public Health, University of California at Berkeley Berkeley, CA

Send reprint requests to Dr. Theodore R. Holford at this address

The application of conditional logistic regression to the analysis of matched case-control studies has now become quite customary. In addition, it is well known that software designed to fit linear logistic and log-linear models can be used in these analyses. The application of conditional logistic regression to cohort designs is described, and an approach is developed that adapts the linear logistic and log-linear models for the analysis of prospectively collected data. Specific situations discussed include matched pairs, 2:1 matching, and studies in which some subjects are pair matched and others matched 2:1. The methods are illustrated with numeric examples.

biometry; epidemiologic methods


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