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dc.contributor.authorLee, Andy
dc.contributor.authorZhao, Yun
dc.contributor.authorYau, Kelvin
dc.contributor.authorNg, Shu
dc.contributor.editorMasahiro Mizuta, Junji Nakano
dc.date.accessioned2017-01-30T15:25:51Z
dc.date.available2017-01-30T15:25:51Z
dc.date.created2009-05-14T02:17:08Z
dc.date.issued2008
dc.identifier.citationLee, Andy and Zhao, Yun and Yau, Kelvin and Ng, Shu. 2008. Survival mixture modelling of recurrent infections, in Mizuta, M. and Nakano, J. (ed), Joint Meeting of 4th World Conference of the IASC and 6th Conference of the Asian Regional Section of the IASC on Computational Statistics and Data Analysis, Dec 5 2008, pp. 1008-1014, Yokohama, Japan: Japanese Society of Computational Statistics.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/46232
dc.description.abstract

Recurrent infections data are commonly encountered in biomedical applications, where the recurrent events are characterised by an acute phase followed by a stable phase after the index episode. Two-component survival mixture models, in both proportional hazards and accelerated failure time settings, are presented as a flexible method of analysing such data. To account for the inherent dependency of the recurrent observations, random effects are incorporated within the conditional hazard function. Assuming a Weibull or log-logistic baseline hazard in both mixture components of the survival mixture model, an EM algorithm is developed for the residual maximum quasi-likelihood estimation of fixed effect and variance components parameters. The methodology is implemented as a graphical user interface coded using Microsoft visual C++. Application to model recurrent urinary tract infections for elderly women is illustrated, where significant individual variations are evident at both acute and stable phases. The survival mixture methodology developed enable practitioners to identify pertinent risk factors affecting the recurrent times and to draw valid conclusions inferred from these correlated and heterogeneous survival data.

dc.publisherJapanese Society of Computational Statistics
dc.titleSurvival mixture modelling of recurrent infections
dc.typeConference Paper
dcterms.source.startPage1008
dcterms.source.endPage1014
dcterms.source.titleProceedings IASC2008
dcterms.source.seriesProceedings of International Association for Statistical Computing "IASC" 2008
dcterms.source.isbn9784990444518
dcterms.source.conferenceJoint Meeting of 4th World Conference of the IASC and 6th Conference of the Asian Regional Section of the IASC on Computational Statistics & Data Analysis
dcterms.source.conference-start-date5 Dec 2008
dcterms.source.conferencelocationPacifico Yokohama, Japan
dcterms.source.placeTokyo, Japan
curtin.note

Copyright © 2008 IASC International Association for Statistical Computing. All right reserved.

curtin.departmentEpidemiology and Biostatistics
curtin.accessStatusOpen access
curtin.facultyFaculty of Health Sciences
curtin.facultySchool of Public Health


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