Exploratory analysis of disease prevalence data from survival/sacrifice experiments

The paper considers the problem of analyzing disease prevalence data from survival experiments in which there may also be some serial sacrifice. The primary objective of the analysis is to describe the composition of the treated and control populations, in terms of age-dependent disease prevalences, by removing distortions in the data caused by the biased nature of the primary sampling mechanism (death). The statistical model which is utilized for this purpose is parameterized in terms of illness state prevalences and lethalities. It does not require determination of cause of death; nor does it assume that diseases progress independently. Methods are presented for estimating various quantities of interest, including disease-specific relative risks and measures of association among diseases. An application of this analysis is shown, using data from a large experiment to investigate the effects of low-level radiation on laboratory mice.