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008			150903s2008 xxu| o |||| 0|eng d
020			_a9780387728353 _99780387728353
024	7		_a10.1007/9780387728353 _2doi
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039		9	_a201509030758 _bVLOAD _c201404122112 _dVLOAD _c201404091843 _dVLOAD _y201402041026 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aQA276-280
100	1		_aDuchateau, Luc. _eautor _9304612
245	1	4	_aThe Frailty Model / _cby Luc Duchateau, Paul Janssen.
264		1	_aNew York, NY : _bSpringer New York, _c2008.
300			_brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
500			_aSpringer eBooks
505	0		_aParametric proportional hazards models with gamma frailty -- Alternatives for the frailty model -- Frailty distributions -- The semiparametric frailty model -- Multifrailty and multilevel models -- Extensions of the frailty model.
520			_aClustered survival data are encountered in many scientific disciplines including human and veterinary medicine, biology, epidemiology, public health and demography. Frailty models provide a powerful tool to analyse clustered survival data. In contrast to the large number of research publications on frailty models, relatively few statistical software packages contain frailty models. It is demanding for statistical practitioners and graduate students to grasp a good knowledge on frailty models from the existing literature. This book provides an in-depth discussion and explanation of the basics of frailty model methodology for such readers. The discussion includes parametric and semiparametric frailty models and accelerated failure time models. Common techniques to fit frailty models include the EM-algorithm, penalised likelihood techniques, Laplacian integration and Bayesian techniques. More advanced frailty models for hierarchical data are also included. Real-life examples are used to demonstrate how particular frailty models can be fitted and how the results should be interpreted. The programs to fit all the worked-out examples in the book are available from the Springer website with most of the programs developed in the freeware packages R and Winbugs. The book starts with a brief overview of some basic concepts in classical survival analysis, collecting what is needed for the reading on the more complex frailty models. Luc Duchateau is Associate Professor of Statistics at the Faculty of Veterinary Medicine of the Ghent University, Belgium. He is board member of the Quetelet Society (Belgian Region of the International Biometric Society) and of the International Biometric Society Channel Network. He has collaborated extensively with physicians in oncology and allergy, public health workers and veterinarians, and is an author of numerous papers in statistical, medical and veterinarian journals. Paul Janssen is Professor of Statistics at the Centre for Statistics of the Hasselt University, Diepenbeek, Belgium. He is an elected member of the International Statistical Institute. He spent research visits at the Johns Hopkins University (Baltimore, USA) and the University of Washington (Seattle, USA). His research interests include survival analysis, nonparametric estimation, resampling techniques and asymptotic theory.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aJanssen, Paul. _eautor _9304613
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9780387728346
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-0-387-72835-3 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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