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Proportional Hazard Regression Model with Bayesian Approach
Authors: Rashmi Aggarwal, Suresh Kumar Sharma, Kanchan Jain
Number of views: 500
The purpose of survival analysis is to model the underlying distribution of the failure
time variable and to assess the dependence of the failure time variable on independent variables. In
this paper, we explored PHREG procedure for different models using Bayesian approach. PHREG
procedure not only fits COX model but also allows us to fit a piecewise exponential model. The
Bayesian analysis treats model parameters as random variables and the inference about these
parameters is based on posterior distribution of the parameters. A posterior distribution is a
weighted likelihood function of the data with a prior distribution of the parameters using the Bayes’
theorem. Generally, for model regression coefficients, normal or uniform prior distributions are used
in PHREG procedure. In addition to this, one may specify gamma or improper prior distribution
for the scale or variance parameters as well as for hazard parameters in piecewise exponential model.
PHREG procedure have been demonstrated with application to real life dataset. Bayesian analysis
with PHREG procedure and piecewise constant Bayesian hazard model is also explored along with
diagnostic test.