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Comparative exposure ratios: A non‐parametric, multifactor technique for case‐control studies
Author(s) -
Aickin Mikel,
Ritenbaugh Cheryl,
Surwit Earl,
Meyskens Frank
Publication year - 1994
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4780130307
Subject(s) - odds ratio , confidence interval , parametric statistics , inference , multivariate statistics , case control study , odds , statistics , measure (data warehouse) , computer science , logistic regression , medicine , mathematics , artificial intelligence , data mining
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. (This research was partially supported by grants from the National Cancer Institute, CA 41108 and CA 25702).