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Am J Epidemiol 2002; 156:463-470.
Copyright © 2002 by the Johns Hopkins Bloomberg School of Public Health

ORIGINAL CONTRIBUTIONS

Effect Heterogeneity by a Matching Covariate in Matched Case-Control Studies: A Method for Graphs-based Representation

Inyoung Kim1, Noah D. Cohen2 and Raymond J. Carroll1

1 Department of Statistics, Texas A&M University, College Station, TX.
2 Department of Large Animal Medicine and Surgery, Texas A&M University, College Station, TX.

The authors describe a method for assessing and characterizing effect heterogeneity related to a matching covariate in case-control studies, using an example from veterinary medicine. Data are from a case-control study conducted in Texas during 1997–1998 of 498 pairs of horses with colic and their controls. Horses were matched by veterinarian and by month of examination. The number of matched pairs of cases and controls varied by veterinarian. The authors demonstrate that there is effect heterogeneity related to this characteristic (i.e., cluster size of veterinarians) for the association of colic with certain covariates, using a moving average approach to conditional logistic regression and graphs-based methods. The method described in this report can be applied to examining effect heterogeneity (or effect modification) by any ordered categorical or continuous covariates for which cases have been matched with controls. The method described enables one to understand the pattern of variation across ordered categorical or continuous matching covariates and allows for any shape for this pattern. This method applies to effect modification when causality might be reasonably assumed.

case-control studies; colic; effect modifiers (epidemiology); epidemiologic methods; heterogeneity; logistic models; multicenter studies


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