000			04197nam a22005055i 4500
001			978-0-387-72835-3
003			DE-He213
005			20250710084016.0
007			cr nn 008mamaa
008			100301s2008 xxu| s |||| 0|eng d
020			_a9780387728353 _a99780387728353
024	7		_a10.1007/978-0-387-72835-3 _2doi
082	0	4	_a519.5 _223
100	1		_aDuchateau, Luc. _eauthor.
245	1	4	_aThe Frailty Model _h[recurso electrónico] / _cby Luc Duchateau, Paul Janssen.
264		1	_aNew York, NY : _bSpringer New York, _c2008.
300			_bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_atext file _bPDF _2rda
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.
650		0	_aSTATISTICS.
650		0	_aONCOLOGY.
650		0	_aEMERGING INFECTIOUS DISEASES.
650		0	_aEPIDEMIOLOGY.
650		0	_aCOMPUTER SIMULATION.
650		0	_aBIOMETRICS.
650	1	4	_aSTATISTICS.
650	2	4	_aSTATISTICS FOR LIFE SCIENCES, MEDICINE, HEALTH SCIENCES.
650	2	4	_aCANCER RESEARCH.
650	2	4	_aSIMULATION AND MODELING.
650	2	4	_aBIOMETRICS.
650	2	4	_aINFECTIOUS DISEASES.
650	2	4	_aEPIDEMIOLOGY.
700	1		_aJanssen, Paul. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387728346
856	4	0	_uhttp://dx.doi.org/10.1007/978-0-387-72835-3 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-SMA
942			_2ddc _cER
999			_c58408 _d58408