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Survival Analysis$
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Shenyang Guo

Print publication date: 2009

Print ISBN-13: 9780195337518

Published to Oxford Scholarship Online: January 2010

DOI: 10.1093/acprof:oso/9780195337518.001.0001

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Multilevel Analysis of Time-to-Event Data

Multilevel Analysis of Time-to-Event Data

Chapter:
(p.116) 6 Multilevel Analysis of Time-to-Event Data
Source:
Survival Analysis
Author(s):

Guo Shenyang

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780195337518.003.0006

This chapter focuses on a relatively new class of survival models: the multilevel approaches to time-to-event data. It first reviews the importance of conducting multilevel analysis in social work research and the recent advances in biostatistics to correct for autocorrelated survival times. It then describes the independent assumption embedded in the Cox proportional hazards model and details the negative consequence of inclusion of autocorrelated data. It reviews available biomedical research models that correct for autocorrelation, particularly the WLW method. Finally, using empirical data, the chapter illustrates how to diagnose the presence of autocorrelation and how to use one such corrective model.

Keywords:   survival models, time-to-event data, multilevel analysis, Cox proportional hazards model, autocorrelation

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