The analysis of pair-matched case-control studies, a multivariate approach.
In matched case-control studies one frequently must consider more than one variable in the analysis and in this paper a log-linear model is presented to meet this objective. A conditional argument yields a method for making inferences on the parameters measuring the association between the variables and disease. The result is similar to the problem of fitting a Bradley-Terry model when one has paired comparisons. Two methods of obtaining maximum conditional likelihood estimates of the parameters are possible: (i) fitting a quasi-independence model in the usual log-linear models context and (ii) fitting a linear logistic model. The results are illustrated with examples.
D000328:Adult; D001334:Automobile Driving; D001722:Birth Order; D002648:Child; D002652:Child Behavior; D004812:Epidemiologic Methods; D006801:Humans; D007405:Intervertebral Disc Displacement / Q000453:epidemiology; D012107:Research Design; D012306:Risk; D013223:Statistics as Topic; D014505:Urban Population