Vary-Coefficient Models for Failure Time Data With Longitudinal Covariates
Date Issued
2005
Date
2005
Author(s)
Hsu, Ming-Chi
DOI
en-US
Abstract
In this thesis, more flexible varying-coefficient hazard models of Cox's type are considered
for failure time data with different settings of longitudinally measured covariates. Here,
a class of smoothing estimation methods are proposed for the parameter functions. Unlike the
former approaches, no distribution assumption is required on the time-dependent
covariates in our estimation methods. As we can see in many biomedical and longitudinal studies,
the collected covariates might have different measured scales. It is impractical to model
the complicated covariate processes, and, hence, the existing methods become very limited in
application. In this study, the asymptotic risks of the proposed estimators are also
established. To examine the finite sample properties of the proposed estimators, a Monte Carlo
simulation is conducted. Finally, an extension of our methods to recurrent event data is
discussed.
Subjects
截切時間
存活時間
風險函數
核估計式
變異係數風險模式
長期追蹤資料
censoring time
failure time
hazard function
kernel estimator
Type
thesis
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