Multilevel multiprocess hazard models are routinely used by demographers to control for endogeneity and selection effects. These models consist of multilevel proportional hazards equations, and possibly probit equations, with correlated random effects. Although Stata currently lacks a specialized command for fitting systems of multilevel proportional hazards models, systems of seemingly unrelated lognormal survival models can be fit with the user-written cmp command (Roodman 2011, Stata Journal 11: 159–206). In this article, we describe multiprocess survival models and demonstrate theoretical and practical aspects of estimation. We also illustrate the application of the cmp command using examples related to demographic research. The examples use a dataset shipped with the statistical software aML.