Parametric regression model for response time in clinical trials – a bayesian approach | Zendy

N. Sundaram | Zendy

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Parametric regression model for response time in clinical trials – a bayesian approach

Author(s) -

N. Sundaram

Publication year - 2017

Publication title -

journal of management and science

Language(s) - English

Resource type - Journals

eISSN - 2250-1819

pISSN - 2249-1260

DOI - 10.26524/jms.2017.1

Subject(s) - markov chain monte carlo , bayesian linear regression , bayesian probability , statistics , mathematics , bayesian statistics , parametric statistics , regression analysis , econometrics , bayesian inference , computer science

In this paper an attempt has been made to model the censored survival data using Bayesian regressions with Markov Chain Monte Carlo (MCMC) methods. Bayesian LogNormal (LN) regression model are found to be providing better fit than the other Bayesian regression models namely Exponential (E), Generalized Exponential (GE), Webull (W), LogLogistic (LL) and Gamma (G).

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