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Activity Number: 665
Type: Contributed
Date/Time: Thursday, August 4, 2016 : 8:30 AM to 10:20 AM
Sponsor: Section on Bayesian Statistical Science
Abstract #320231 View Presentation
Title: AFT Modeling of Misclassified Clustered Interval-Censored Data
Author(s): Alejandro Jara* and María José García-Zattera and Arnost Komarek
Companies: Pontificia Universidad Católica de Chile and Pontificia Universidad Católica de Chile and Charles University in Prague
Keywords: Multivariate survival data ; Mismeasured continuous response

Motivated by a longitudinal oral health study, we propose a modelling approach for clustered time-to-event data, when the response of interest can only be determined to lie in an interval obtained from a sequence of examination times and the determination of the occurrence of the event is subject to misclassification. The clustered time-to-event data are modelled using an accelerated failure time model with random effects and by assuming a penalised Gaussian mixture model for the random effects terms to avoid restrictive distributional assumptions. A general misclassification model is discussed in detail, considering the possibility that different examiners were involved in the assessment of the occurrence of the events for a given subject across time. We additionally provide empirical evidence showing that the model can be used to estimate the underlying time-to-event distribution and the misclassification parameters without any external information about the latter parameters. We also provide results of a simulation study. A. Jara's research is supported by Fondecyt grant 1141193. M.J. Garcia-Zattera's research is supported by Fondecyt grant 11110033.

Authors who are presenting talks have a * after their name.

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