Abstract/Details

Incorporating time -dependent covariates in the Cox proportional hazards model: The LVAR approach


2005 2005

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Abstract (summary)

In survival analysis, use of the Cox proportional hazards model requires knowledge of all covariates under consideration at every failure time. Since failure times rarely coincide with observation times, time-dependent covariates need to be inferred from the observed values. In this dissertation, we consider an auto-correlated covariate process with random subject effect and measurement error and introduce the last value auto-regressed (LVAR) estimation method. We investigate the performance of this approach in different situations and compare it to several other established estimation approaches via a simulation study. The comparison shows this method results in a smaller mean square error over a large number of scenarios when considering the time-dependent covariate effect. A model selection procedure is also suggested to make LVAR approach more flexible. This approach is applied to a real problem involving Primary Biliary Cirrhosis data from the Mayo clinic. The application shows that LVAR results in stronger effects of log albumin and log prothromin time than several published methods.

Indexing (details)


Subject
Statistics
Classification
0463: Statistics
Identifier / keyword
Pure sciences; Proportional hazards; Time-dependent covariates
Title
Incorporating time -dependent covariates in the Cox proportional hazards model: The LVAR approach
Author
Liu, Yali
Number of pages
112
Publication year
2005
Degree date
2005
School code
0183
Source
DAI-B 66/08, Dissertation Abstracts International
Place of publication
Ann Arbor
Country of publication
United States
ISBN
0542276917, 9780542276910
Advisor
Craig, Bruce A.
University/institution
Purdue University
University location
United States -- Indiana
Degree
Ph.D.
Source type
Dissertations & Theses
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
3185798
ProQuest document ID
305426269
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Document URL
http://search.proquest.com/docview/305426269/abstract
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