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.
journal_name
Math Bioscijournal_title
Mathematical biosciencesauthors
Wienke A,Arbeev KG,Locatelli I,Yashin AIdoi
10.1016/j.mbs.2004.11.010subject
Has Abstractpub_date
2005-11-01 00:00:00pages
1-13issue
1eissn
0025-5564issn
1879-3134pii
S0025-5564(05)00029-5journal_volume
198pub_type
杂志文章abstract：:Modeling a cell's response to encroaching ice has informed the development of cryopreservation protocols for four decades. It has been well documented that knowledge of the cellular state as a function of media and cooling rate faciliate informed cryopreservation protocol design and explain mechanisms of damage. Howev...
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