Kazeem Adeleke , Obafemi Awolowo University
In this paper, we consider modeling a right censored time to event data under the purview of CD4 cell count (HID/AIDS disease marker) using Bayesian methods of statistical inference to estimate the cured or long-term survivors. The number of competing cause (CD4) follows a Compound Poisson distribution for the number of competing cause (CD4) and a logistic link for reparametrization of cured fraction through the covariate. A MCMC method is develop to analyze the proposed model. We examine the performances of the proposed models and method via simulation and apply them to analyze the HIV/AIDS data set from ART centers, LUTH, Lagos, Nigeria.
Presented in Session P2. Poster Session Ageing, Health and Mortality