Parametric joint modelling for longitudinal and survival data

Pericleous, Paraskevi (2016) Parametric joint modelling for longitudinal and survival data. Doctoral thesis, University of East Anglia.

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Abstract

Joint modelling is the simultaneous modelling of longitudinal and survival data,
while taking into account a possible association between them. A common approach
in joint modelling studies is to assume that the repeated measurements follow a lin-
ear mixed e�ects model and the survival data is modelled using a Cox proportional
hazards model. The Cox model, however, requires a strong proportionality assump-
tion, which seems to be violated quite often. We, thus, propose the use of parametric
survival models. Additionally, joint modelling literature mainly deals with right-
censoring only and does not consider left-truncation, which can cause bias. The joint
model proposed here considers left-truncation and right-censoring.

Item Type:	Thesis (Doctoral)
Faculty \ School:	Faculty of Science > School of Computing Sciences
Depositing User:	Users 7376 not found.
Date Deposited:	23 Aug 2016 11:33
Last Modified:	23 Aug 2016 11:33
URI:	https://ueaeprints.uea.ac.uk/id/eprint/59673
DOI:

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