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Joint Model of Longitudinal Count and Time to Event Data with Excess Zeros Using the AFT Model: A Case Study of the HIV/ AIDS Dataset
Ehsan Bahrami Samani , Mojtaba Zeinali
Abstract:   (220 Views)
This article aims to joint modeling of longitudinal CD4 cells count and time to death in HIV patients based on the AFT model. The modeling of the longitudinal count response, a GLME model under the family of PSD, was used. In contrast, for the TTE data, the parametric AFT model under the Weibull distribution was investigated. These two responses are linked through random effects correlated with the normal distribution. The longitudinal and survival data are then assumed independent, given the latent linking process and any available covariates. Considering excess zeros for two responses and right censoring, presented a joint model that has not yet been investigated by other researchers. The parameters were also estimated using MCMC methods.
Keywords: Accelerated Failure Time Model, Time to Event, Right Censoring, Family of Power Series Distribution, Generalized Linear Mixed Effect (GLME) Model.
Full-Text [PDF 5803 kb]   (4 Downloads)    
Type of Study: Research | Subject: Applied Statistics
Received: 2020/03/3 | Accepted: 2020/09/19
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مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences
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