Abstract
Some clinical investigations of irreversible chronic diseases begin with a sample of healthy subjects and follow them through the process of disease onset and death. Researchers often ask if the presence of the disease diminishes a person's life expectancy. When parametric models are used for the analysis, hypotheses about the death rates for those people with and without the disease are usually tested by means of standard normal tests on the difference in the parameter estimates or by likelihood-ratio chi-square tests. This paper uses Monte Carlo simulation techniques to examine the precision of parameter estimates and the power of these tests for a model used for a previous study of senile dementia, Alzheimer's type.
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