Bayesian Analysis of Markov Based Logistic Model

Authors

  • Soma Chowdhury Biswas Department of Statistics, University of Chittagong, Chittagong, Bangladesh
  • Janardan Mahanta Department of Statistics, University of Chittagong, Chittagong, Bangladesh
  • Manindra Kumar Roy Ranada Prasad Shaha University, Narayanganj, Bangladesh

DOI:

https://doi.org/10.6000/1929-6029.2018.07.02.4

Keywords:

Bayesian approach, Bayes Factor (BF), Linear exponential (LINEX), Longitudinal data, Markov model, Modified linear exponential (MLINEX).

Abstract

In analyzing longitudinal data the correlations between responses obtained from same individual need to be taken into account. Various models can be used to handle such correlations. This article focuses on the application of transition modeling using Bayesian approach for analyzing longitudinal binary data. For Bayesian estimation asymmetric loss functions, such as, linear exponential (LINEX) and modified linear exponential (MLINEX) loss function and Tierney and Kadnae (T.K.) approximation has been used. Comparison is made using Bayes factor and Bayesian approach under LINEX loss function can be suggested to estimate the parameters of transition model.

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Published

2018-05-08

Issue

Section

General Articles

How to Cite

Bayesian Analysis of Markov Based Logistic Model. (2018). International Journal of Statistics in Medical Research, 7(2), 57-65. https://doi.org/10.6000/1929-6029.2018.07.02.4

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