Abstract
Cure models are a special type of survival analysis model where it is assumed that there are a proportion of subjects who will never experience the event and thus the survival curve will eventually reach a plateau. In population-based cancer studies, cure is said to occur when the mortality (hazard) rate in the diseased group of individuals returns to the same level as that expected in the general population. The cure fraction is of interest to patients and a useful measure to monitor trends and differences in survival of curable disease. I will describe the strsmix and strsnmix commands, which fit the two main types of cure fraction model, namely, the mixture and nonmixture cure fraction models. These models allow incorporation of the expected background mortality rate and thus enable the modeling of relative survival when cure is a possibility. I give an example to illustrate the commands.
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More From: The Stata Journal: Promoting communications on statistics and Stata
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