A continuous-time Markov chain approach with the analytic likelihood in studies of behavioral changes

Ho-Lan Peng, Andrew Aschenbrenner, Kirk von Sternberg, Patricia D. Mullen and Wenyaw Chan

Communications in Statistics - Theory and Methods, 2019, vol. 48, issue 23, 5756-5765

Abstract: We develop an analytic likelihood approach for a four-state CTMC by solving the backwards Kolmogorov differential equations, reducing this bias in transition rate estimates. A simulation study is performed to assess the performance of this new method and confirms that it achieves good coverage probabilities with low bias and standard errors. Finally, we analyzed data from Project SUCCESS to estimate the study each participant’s transitions among behavioral stage, consisting of risky drinking and possible ineffective using of contraception, which comprise the primary endpoint of risk of an alcohol-exposed pregnancy.

Date: 2019
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2018.1520886 (text/html)
Access to full text is restricted to subscribers.

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:taf:lstaxx:v:48:y:2019:i:23:p:5756-5765

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2018.1520886

Access Statistics for this article

Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe

More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().