Recent developments in discrete-time multistate estimation in Stata

Daniel C. Schneider
Additional contact information
Daniel C. Schneider: Max Planck Institute for Demographic Research

German Stata Conference 2025 from Stata Users Group

Abstract: Multistate life tables (MSLTs), or multistate survival models, have become a widely used analytical framework in the social and health sciences. These models can be cast in continuous or discrete time. The dtms Stata module (dtms stands for "discretetime multistate"), which was presented at the German Stata Conference 2023 (Schneider 2023), implements the estimation of the discrete-time flavor of these models. This presentation first outlines discrete-time multistate estimation and then gives an overview of recent package enhancements including the following: external multinomial logistic estimation results, for example, from the interpolated Markov chain (IMaCh) executable (Brouard 2021), can be imported for further processing; difficulties with reloading saved dtms files across package versions have been resolved; the initial state distribution has been incorporated into the asymptotic analysis; new result type “evol” calculates the evolution of population fractions, along with the corresponding covariance matrix; estimation based on restricted transitions has been improved; transition probabilities can be based on time-varying covariate values; and several dtms trees can now be held in memory.

Date: 2025-04-26
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://repec.org/dsug2025/Germany25_Schneider.pdf

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:boc:dsug25:08

Access Statistics for this paper

More papers in German Stata Conference 2025 from Stata Users Group Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F Baum ().