Regression Analysis of Tumour Prevalence Data

Gregg E. Dinse and S. W. Lagakos

Journal of the Royal Statistical Society Series C, 1983, vol. 32, issue 3, 236-248

Abstract: This paper proposes a logistic regression model for comparing treatment groups with respect to tumour prevalence. The prevalence test commonly used to compare treatments in animal tumorigenicity experiments (Hoel and Walburg, 1972; Peto et al., 1980) is essentially equivalent to a likelihood score test derived under a logistic model that expresses tumour prevalence as a function of time and treatment. The more general regression context suggests an alternative to the convention of grouping observations into arbitrarily chosen intervals. The model also incorporates covariates, provides a framework for estimating the strength of a dose‐response relationship and for testing a central assumption underlying the usual prevalence test, and is computationally simple to analyse.

Date: 1983
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