Analysis of recurrent events with associated informative censoring: application to HIV data

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dc.contributor.authorEjoku, Jonathan
dc.date.accessioned2021-07-28T13:40:06Z
dc.date.available2021-07-28T13:40:06Z
dc.date.issued2020-06
dc.descriptionA Thesis submitted in partial fulfillment of the requirements for the Degree of Master of Science in Statistical Sciences (MSc. SS) at Strathmore Universityen_US
dc.description.abstractIn this study, we adapt a commonly used Cox-based model for recurrent events; the Prentice, Williams and Peterson Total -Time (PWP-TT) that has been largely used under the assumption of non-informative censoring and evaluate it under an informative censoring setting. Empirical evaluation was undertaken with the aid of the semi-parametric framework for recurrent events suggested by (Huang and Wang, 2004) where a subject speci c latent variable is used to model the association between the recurrent event and hazard of the failure time. All implementations were made in R Studio software, using the reReg package (Chiou and Huang, 2019) and the method in the reReg function set to 'cox.HW'. For validation we used HIV data from a typical HIV care setting in Kenya. Results show that the PWP-TT model generally t the data well, with a comparison to the Andersen-Gill method showing similar estimates, while the ordinary Cox model estimates were too unreliableen_US
dc.description.sponsorshipStrathmore Institute of Mathematical Sciencesen_US
dc.identifier.urihttp://hdl.handle.net/11071/12054
dc.language.isoen_USen_US
dc.publisherStrathmore Universityen_US
dc.subjectRecurrent eventsen_US
dc.subjectLoss to follow-upen_US
dc.subjectHIVen_US
dc.subjectInformative censoringen_US
dc.titleAnalysis of recurrent events with associated informative censoring: application to HIV dataen_US
dc.typeThesisen_US
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MSc.SS Theses and Dissertations (2020)