Journal of Statistics Applications & Probability

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Data often arrive with hierarchical structure and multilevel regression modeling is the most popular approach to handle such data. This paper demonstrates how multilevel model can be analyzed in Bayesian framework, with reference to a practical degradation data problem. Assuming a varying-intercept, varying-slope model for the data, the exact as well as the approximate inference procedures have been developed using R and JAGS and their performance have been compared. Further, the concept of Bayesian p-values have been discussed to assess the adequacy of the proposed model.

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