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Estimation of multiprocess survival models with cmp

Author

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  • Tamas Bartus

    (Corvinus University of Budapest)

  • David Roodman

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). 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. Copyright 2014 by StataCorp LP.

Suggested Citation

  • Tamas Bartus & David Roodman, 2014. "Estimation of multiprocess survival models with cmp," Stata Journal, StataCorp LP, vol. 14(4), pages 756-777, December.
    • Handle: RePEc:tsj:stataj:v:14:y:2014:i:4:p:756-777
    Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj14-4/st0358/
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    Cited by:

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    2. Maria Esther Oswald-Egg & Ursula Renold, 2019. "No Experience, No Employment: The Effect of Vocational Education and Training Work Experience on Labour Market Outcomes after Higher Education," KOF Working papers 19-469, KOF Swiss Economic Institute, ETH Zurich.
    3. John T. Addison & Paulino Teixeira & Katalin Evers & Lutz Bellmann, 2017. "Contract Innovation in Germany: An Economic Evaluation of Pacts for Employment and Competitiveness," British Journal of Industrial Relations, London School of Economics, vol. 55(3), pages 500-526, September.
    4. Øystein Kravdal, 2019. "Taking birth year into account when analysing effects of maternal age on child health and other outcomes: The value of a multilevel-multiprocess model compared to a sibling model," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 40(43), pages 1249-1290.
    5. Marie Bouchard & Damien Rousselière, 2018. "Does Gibrat's law hold among urban social economy enterprises? A research note on Montreal social economy," Economics Bulletin, AccessEcon, vol. 38(3), pages 1523-1540.
    6. Oswald-Egg, Maria Esther & Renold, Ursula, 2021. "No experience, no employment: The effect of vocational education and training work experience on labour market outcomes after higher education," Economics of Education Review, Elsevier, vol. 80(C).
    7. Tuan Nguyen‐Anh & Shawn Leu & Anh Nguyen‐Thi‐Phuong & Thanh Ngo‐Dang & Nguyen To‐The, 2023. "Adapting to the new normal: A sustainable livelihood framework for the informal sectors during COVID‐19," Review of Development Economics, Wiley Blackwell, vol. 27(2), pages 1092-1112, May.
    8. Chongyang Chen & Robert Kieschnick, 2024. "Bank competition and the design of syndicated loans," The Financial Review, Eastern Finance Association, vol. 59(1), pages 227-251, February.
    9. Zsolt Spéder & Tamás Bartus, 2017. "Educational Enrolment, Double-Status Positions and the Transition to Motherhood in Hungary," European Journal of Population, Springer;European Association for Population Studies, vol. 33(1), pages 55-85, February.
    10. Cumming, Douglas & Meoli, Michele & Vismara, Silvio, 2019. "Investors’ choices between cash and voting rights: Evidence from dual-class equity crowdfunding," Research Policy, Elsevier, vol. 48(8), pages 1-1.
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