2014
DOI: 10.1177/1536867x1401400404
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Estimation of Multiprocess Survival Models with cmp

Abstract: 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). I… Show more

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Cited by 21 publications
(12 citation statements)
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“…The multi-level, multi-equation modeling framework accommodates the joint estimation of hazard and probit equations to account for the endogeneity of dummy explanatory variables that appear in the hazard equation of primary interest (Lillard et al, 1995). The joint estimation accounts for the correlation of the random effects and allows us to control for the effects of unobserved offering features (Bartus and Roodman, 2014).…”
Section: Post-offering Outcomesmentioning
confidence: 99%
“…The multi-level, multi-equation modeling framework accommodates the joint estimation of hazard and probit equations to account for the endogeneity of dummy explanatory variables that appear in the hazard equation of primary interest (Lillard et al, 1995). The joint estimation accounts for the correlation of the random effects and allows us to control for the effects of unobserved offering features (Bartus and Roodman, 2014).…”
Section: Post-offering Outcomesmentioning
confidence: 99%
“…We implement a multivariate sample selection model, also known as a generalised Heckman model, generalised from Amemiya (1974), and Heckman (1979) using n equations. This is also a special case of the more general ‘multilevel multiprocess model’ (Bartus & Roodman, 2014). We use the CMP (conditional mixed process) framework proposed by Roodman (2011) which relies on an efficient simulated maximum likelihood algorithm to estimate a system of simultaneous equations.…”
Section: Methodsmentioning
confidence: 99%
“…As we estimate both individual and institutional drivers of alcohol consumption, a traditional approach would consist in a multilevel model with fixed or random effects. However, in our case, it would lead to an intractable model, as the estimation time exponentially increases with the number of parameters (Bartus and Roodman, 2014). We have, therefore, two possible options.…”
Section: Econometric Strategymentioning
confidence: 99%
“…The system of equations is estimated using the conditional mixed process (CMP) estimator of Stata software [28,31]. The CMP is a flexible tool to estimate systems of equations with various link functions [33]. Then, we can consistently estimate parameters of Equations (3) and (4) by using CMP [31] as follows:…”
Section: Materials and Methodologymentioning
confidence: 99%