Frailty models and frailty-mixture models for recurrent event times
Ying Xu
Center for Quantitative Medicine
Duke–NUS Graduate Medical School
Singapore
and
Department of Biostatistics
Singapore Clinical Research Institute
Singapore
[email protected]
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Yin Bun Cheung
Center for Quantitative Medicine
Duke–NUS Graduate Medical School
Singapore
and
Department of International Health
University of Tampere
Finland
[email protected]
|
Abstract. The analysis of recurrent event times faces three challenges: betweensubject
heterogeneity (frailty), within-subject event dependence, and the possibility
of a cured fraction. Frailty can be handled by including a latent
random-effects term in a Cox-type model. Event dependence may be considered as
contributing to the intervention effect, or it may be considered as a source of
nuisance, depending on the analysts’ specific research questions. If it is seen
as a nuisance, the analysis can stratify the recurrent event times according to
event order. If it is seen as contributing to the intervention effect,
stratification should not be used. Models with and without stratification for
event order estimate two types of treatment effects. They are analogous to
per-protocol analysis and intention-to-treat analysis, respectively. In the
context of chronic disease treatment, we want to estimate whether there is a
cured fraction; for infectious disease prevention, this is called a
nonsusceptible fraction. In infectious disease prevention, we want to
understand whether an intervention protects each of its recipients to some
extent (“leaky” model) or whether it totally protects some recipients but
offers no protection to the rest (“all-or-none” model). The truth may be a
mixture of the two modes of protection. We describe a class of regression
models that can handle all three issues in the analysis of recurrent event
times. The model parameters are estimated by the expectation-maximization
algorithm, and their variances are estimated by Louis’s formula. We provide a
new command, strmcure, for implementing these models.
View all articles by these authors:
Ying Xu, Yin Bun Cheung
View all articles with these keywords:
strmcure, frailty models, frailty-mixture models, recurrent event times, event dependence, cured fraction
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