An expanded framework for mixed process modeling in Stata

Roodman (Stata Journal, 2011) introduced the program cmp for using maximum likelihood to fit multiequation combinations of Gaussian-based models such as tobit, probit, ordered probit, multinomial probit, interval censoring, and continuous linear. This presentation describes substantial extensions to the framework and software: factor variable support; the rank-ordered probit model; the ability to specify precensoring truncation in most model types; hierarchical random effects and coefficients that are potentially correlated across equations; the ability to include the unobserved linear variables behind endogenous variables—not just their observed, censored manifestations—on the right side of other equations and, when so doing, the allowance for simultaneity in the system of equations. Contrary to the title of Roodman (2011), models no longer need be recursive or fully observed.