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2014 | 15 | nr 3 | 437--452
Tytuł artykułu

Joint Longitudinal and Survival Data Modelling : an Application in Anti-Diabetes Drug Therapeutic Effect

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The longitudinal and survival analyses are useful tools in the exploration of drug trial data. In both cases the challenge is to deal with correlated repeated observations. Here, the joint modelling for longitudinal and survival data has been carried out via Markov chain Monte Carlo (MCMC) method in type 2 diabetes clinical trials to compare different combinations of drugs, viz. Metformin plus Pioglitazone and Gliclazide plus Pioglitazone. Despite the complexity of the model it has been found relatively easier to implement with WinBugs software. The results have been computed and compared with software R. In both types of the analyses it has been found that no estimates of treatment appear to have significant effect on the evolution of the matter of HBAlc, neither on the longitudinal part nor on the survival one. The Bayesian approach has been considered as an extended tool with classical approach for estimation of clinical trial data analysis. (original abstract)
Opis fizyczny
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