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Autor
Pandey Arvind (Central University of Rajasthan, India), Hanagal David D. (Savitribai Phule Pune University, India), Tyagi Shikhar (Central University of Rajasthan, India)
Tytuł
Generalised Lindley Shared Additive Frailty Regression Model for Bivariate Survival Data
Źródło
Statistics in Transition, 2022, vol. 23, nr 4, s. 161-176, aneks, tab., bibliogr. 40 poz.
Słowa kluczowe
Estymacja bayesowska, Estymacja, Metody statystyczne
Bayesian estimation, Estimation, Statistical methods
Uwagi
summ.
Abstrakt
Frailty models are the possible choice to counter the problem of the unobserved heterogeneity in individual risks of disease and death. Based on earlier studies, shared frailty models can be utilised in the analysis of bivariate data related to survival times (e.g. matched pairs experiments, twin or family data). In this article, we assume that frailty acts additively to the hazard rate. A new class of shared frailty models based on generalised Lindley distribution is established. By assuming generalised Weibull and generalised log-logistic baseline distributions, we propose a new class of shared frailty models based on the additive hazard rate. We estimate the parameters in these frailty models and use the Bayesian paradigm of the Markov Chain Monte Carlo (MCMC) technique. Model selection criteria have been applied for the comparison of models. We analyse kidney infection data and suggest the best model. (original abstract)
Dostępne w
Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie
Biblioteka SGH im. Profesora Andrzeja Grodka
Biblioteka Główna Uniwersytetu Ekonomicznego w Katowicach
Pełny tekst
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Bibliografia
Pokaż
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Cytowane przez
Pokaż
ISSN
1234-7655
Język
eng
URI / DOI
http://dx.doi.org/10.2478/stattrans-2022-0048
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