A comparison of different bivariate correlated frailty models and estimation strategies.

TitreA comparison of different bivariate correlated frailty models and estimation strategies.
Publication TypeJournal Article
Year of Publication2005
AuthorsWienke, A, Arbeev, KG, Locatelli, I, Yashin, AI
JournalMath Biosci
Volume198
Issue1
Pagination1-13
Date Published2005 Nov
DOI10.1016/j.mbs.2004.11.010
ISSN0025-5564
Mots-clésBayes Theorem, Computer Simulation, Likelihood Functions, Markov Chains, Models, Statistical, Monte Carlo Method, Multivariate Analysis, Numerical Analysis, Computer-Assisted
Abstract

Frailty models are becoming increasingly popular in multivariate survival analysis. Shared frailty models in particular are often used despite their limitations. To overcome their disadvantages numerous correlated frailty models were established during the last decade. In the present study, we examine bivariate correlated frailty models, and especially the behavior of the parameter estimates when using different estimation strategies. We consider three different bivariate frailty models: the gamma model and two versions of the log-normal model. The traditional maximum likelihood procedure of parameter estimation in the gamma case with an explicit available likelihood function is compared with maximum likelihood methods based on numerical integration and a Bayesian approach using MCMC methods with the help of a comprehensive simulation study. We detected a strong dependence between the two parameter estimates (variance and correlation of frailties) in the bivariate correlated frailty model and analyzed this dependence in detail.

Notes

SAPHIRID:58628

Alternate URL

http://www.ncbi.nlm.nih.gov/pubmed/16185720?dopt=Abstract

Alternate JournalMath Biosci
Citation Key / SERVAL ID2330
PubMed ID16185720
Grant List7P01AG08761-09 / AG / NIA NIH HHS / United States

                         

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