This paper develops Bayesian analysis for Constant Stress Accelerated
Life Test (CSALT) under Type-II censoring scheme. Failure times
are assumed to distribute as the three-parameter Generalized Logistic
(GL) distribution. The inverse power law model is used to represent
the relationship between the stress and the scale parameter of a test
unit. Bayes estimates are obtained using Markov Chain Monte Carlo
(MCMC) simulation algorithm based on Gibbs sampling. Then, confidence
intervals, and predicted values of the scale parameter and the
reliability function under usual conditions are obtained. Numerical illustration
and an illustrative example are addressed for illustrating the
theoretical results. WinBUGS software package is used for implementing
Markov Chain Monte Carlo (MCMC) simulation and Gibbs sampling.