Literature DB >> 21786277

Frailty models: Applications to biomedical and genetic studies.

Usha S Govindarajulu1, Haiqun Lin, Kathryn L Lunetta, R B D'Agostino.   

Abstract

In survival analysis, frailty models are potential choices for modeling unexplained heterogeneity in a population. This tutorial presents an overview and general framework of frailty modeling and estimation for multiplicative hazards models in the context of biomedical and genetic studies. Other topics in frailty models, such as diagnostic methods for model adequacy and inference in frailty models, are also discussed. Examples of analyses using multivariate frailty models in a non-parametric hazards setting on biomedical datasets are provided, and the implications of choosing to use frailty and relevance to genetic applications are discussed.
Copyright © 2011 John Wiley & Sons, Ltd.

Mesh:

Year:  2011        PMID: 21786277     DOI: 10.1002/sim.4277

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  19 in total

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2.  An approach to addressing selection bias in survival analysis.

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Authors:  Marie Vigan; Jérôme Stirnemann; France Mentré
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8.  Elevated preoperative CEA is associated with worse survival in stage I-III rectal cancer patients.

Authors:  I Tarantino; R Warschkow; M Worni; K Merati-Kashani; D Köberle; B M Schmied; S A Müller; T Steffen; T Cerny; U Güller
Journal:  Br J Cancer       Date:  2012-06-26       Impact factor: 7.640

9.  Patterns and Trends of Polybrominated Diphenyl Ethers in Bald Eagle Nestlings in Minnesota and Wisconsin, USA.

Authors:  William T Route; Cheryl R Dykstra; Sean M Strom; Michael W Meyer; Kelly A Williams
Journal:  Environ Toxicol Chem       Date:  2021-03-10       Impact factor: 3.742

10.  Learning Bayesian Networks from Correlated Data.

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