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Autor
Bhattacharjee Atanu (Malabar Cancer Centre), Nath Dilip C. (Gauhati University, Indie)
Tytuł
Joint Longitudinal and Survival Data Modelling : an Application in Anti-Diabetes Drug Therapeutic Effect
Źródło
Statistics in Transition, 2014, vol. 15, nr 3, s. 437-452, rys., tab., bibliogr. 33 poz.
Słowa kluczowe
Metoda Monte Carlo, Łańcuch Markowa, Medycyna, Analiza statystyczna
Monte Carlo method, Markov chain, Medicine, Statistical analysis
Uwagi
summ.
Abstrakt
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)
Dostępne w
Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie
Biblioteka SGH im. Profesora Andrzeja Grodka
Biblioteka Główna Uniwersytetu Ekonomicznego w Katowicach
Biblioteka Główna Uniwersytetu Ekonomicznego we Wrocławiu
Pełny tekst
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Bibliografia
Pokaż
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ISSN
1234-7655
Język
eng
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