Title: Conditional regression analysis of the exposure-disease odds ratio using known probability-of-exposure values.
Authors: Satten, G A; Kupper, L L
Published In Biometrics, (1993 Jun)
Abstract: Conditional inference methods are proposed for the odds ratio between binary exposure and disease variables when only the probability of exposure is known for each study subject. We develop a conditional likelihood approach that removes nuisance parameters and permits inferences to be made about important parameters in log odds ratio regression models. We also discuss a heuristic procedure based on estimating the (unknown) number of truly exposed individuals; this procedure provides a simple framework for interpreting our likelihood-based statistics, and leads to a Mantel-Haenszel-type estimator and a goodness-of-fit test. As an example of the use of this methodology, we present an analysis of some genetic data of Swift et al. (1976, Cancer Research 36, 209-215).
PubMed ID: 8369379
MeSH Terms: No MeSH terms associated with this publication