Comparative exposure ratios: a non-parametric, multifactor technique for case-control studies.
The odds ratio in a two-by-two table is widely used in case-control studies to measure association between disease and a binary risk factor. In this article we propose a more general measure of association, the comparative exposure ratio (CER), which is the ratio of the number of case-control pairs where the case has greater exposure divided by the number where the control has greater exposure. In simple cases, the CER is an odds ratio or a weighted combination of odds ratios. In more general cases, a CER continues to measure association even when an odds ratio computation is not feasible. Moreover, CERs improve on odds ratios in several ways: they do not require binary risk factors, or a choice of the scale of measurement of continuous risk factors; they make it possible to investigate multiple risk factors simultaneously, without multivariate parametric assumptions; they also can be used to detect patterns that might indicate possible causal pathways. We illustrate how various choices of the definition of 'greater exposure' make the CER a powerful and flexible tool. We give expressions for confidence intervals for CERs, and verify in a pilot simulation that they are valid. Finally, we illustrate with a case-control study of cervical dysplasia how exploratory inference using CERs can be carried out.
Aickin
M
M
Department of Family and Community Medicine, University of Arizona, Tucson 85724.
Ritenbaugh
C
C
Surwit
E
E
Meyskens
F
F
D016022:Case-Control Studies; D015984:Causality; D016001:Confidence Intervals; D004032:Diet / Q000009:adverse effects; D005260:Female; D006801:Humans; D016015:Logistic Models; D015999:Multivariate Analysis; D016017:Odds Ratio; D010865:Pilot Projects; D015203:Reproducibility of Results; D012107:Research Design; D012307:Risk Factors; D012907:Smoking / Q000009:adverse effects; D002578:Uterine Cervical Dysplasia / Q000453:epidemiology / Q000209:etiology