Multilevel multiprocess modeling with gsem
Tamás Bartus
Stata Journal, 2017, vol. 17, issue 2, 442-461
Abstract:
Multilevel multiprocess models are simultaneous equation systems that include multilevel hazard equations with correlated random effects. Demog- raphers routinely use these models to adjust estimates for endogeneity and sample selection. In this article, I demonstrate how multilevel multiprocess models can be fit with the gsem command. I distinguish between two classes of multilevel multiprocess models: nonrecursive systems of hazard equations without observed endogenous variables and recursive systems that include a hazard equation with ob- served endogenous qualitative variables. I illustrate the estimation of both classes of models using sample datasets shipped with the statistical software aML. I pay special attention to identifying structural coefficients in nonrecursive simultaneous systems.
Keywords: survival analysis; multilevel multiprocess models; multilevel analysis; simultaneous equations; endogeneity; gsem (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (7)
Downloads: (external link)
http://www.stata-journal.com/article.html?article=st0481 link to article purchase
http://www.stata-journal.com/software/sj17-2/st0481/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:tsj:stataj:v:17:y:2017:i:2:p:442-461
Ordering information: This journal article can be ordered from
http://www.stata-journal.com/subscription.html
Access Statistics for this article
Stata Journal is currently edited by Nicholas J. Cox and Stephen P. Jenkins
More articles in Stata Journal from StataCorp LLC
Bibliographic data for series maintained by Christopher F. Baum () and Lisa Gilmore ().