Frailty models and frailty-mixture models for recurrent event times: Update
Ying Xu
Center for Quantitative Medicine
Duke–NUS Graduate Medical School
and Procter & Gamble Co.
Singapore, Singapore
tinayxu@gmail.com
|
Yin Bun Cheung
Center for Quantitative Medicine
Duke–NUS Graduate Medical School
Singapore, Singapore
and Department for International Health
University of Tampere
Tampere, Finland
yinbun.cheung@duke-nus.edu.sg
|
Abstract. Xu and Cheung (2015, Stata Journal 15: 135–154) introduced the
strmcure command, which fits frailty models and frailty-mixture models in the
analysis of recurrent event times. In this article, we provide an update to strmcure.
The update implements a two-step estimation procedure for a frailty-mixture
model that allows the estimation of the effect of an intervention on the probability
of cure and on the total effect on event rate in the noncured. To illustrate, we
will use the same example dataset on respiratory exacerbations from the original
article.
View all articles by these authors:
Ying Xu, Yin Bun Cheung
View all articles with these keywords:
strmcure, frailty-mixture model, primary effect, total effect, two-step estimation procedure
Download citation: BibTeX RIS
Download citation and abstract: BibTeX RIS
|
