Split-population model (cure model, long-term survivor model)

When there are a portion of respondents who will never experience the event (immortal), ordinary survival modeling techniques are not adequate. Special models designed to handle this kind of situations are called split-population model, cure model, or long-term survivor model.

aML does not handle split-population model; Mplus handles it by imposing constraints on a two-class mixture model; Stata has the following some facilities:

1. lncure: log-normal model with split-population;
2. spsurv: discrete time split-population model;
3. cureregr: split-population model with weibull, lognormal, logistic, gamma, and exponential distribution;
4. strxmix and strsnmix: split-population model with weibull, lognormal, gamma, and some mixture distribution.

Among the above, 1-3 are not well documented, while 4 is described in the most recent issue of Stata Journal (7-3).

For discrete-time models, there are only two alternatives: Mplus or spsurv.