000			03967nam a2200397 a 4500
999			_c6531 _d6531
001			.b41053333
003			OSt
005			20210406161546.0
008			081211s2008 xxuad|| fb|||0|1 0 eng|c
020			_a9780471754992
040			_aES-BaCBU _bcat _cES-BaCBU _dOSt
041			_aeng
080			_a311:314
100	1		_aHOSMER, David W. _96813
245	1	0	_aApplied survival analysis : _bregression modeling of time to event data / _cDavid W. HOSMER, Stanley LEMESHOW, Susanne MAY
250			_a2a ed.
260			_aNew York [etc.] : _bWiley, _ccop. 2008
300			_axiii, 392 p. : _bgràf., taules ; _c25 cm
504			_aInclou referències bibliogràfiques i índex.
520			_aSince publication of the first edition nearly a decade ago, analyses using time-to-event methods have increase considerably in all areas of scientific inquiry mainly as a result of model-building methods available in modern statistical software packages. However, there has been minimal coverage in the available literature to9 guide researchers, practitioners, and students who wish to apply these methods to health-related areas of study. Applied Survival Analysis, Second Edition provides a comprehensive and up-to-date introduction to regression modeling for time-to-event data in medical, epidemiological, biostatistical, and other health-related research. This book places a unique emphasis on the practical and contemporary applications of regression modeling rather than the mathematical theory. It offers a clear and accessible presentation of modern modeling techniques supplemented with real-world examples and case studies. Key topics covered include: variable selection, identification of the scale of continuous covariates, the role of interactions in the model, assessment of fit and model assumptions, regression diagnostics, recurrent event models, frailty models, additive models, competing risk models, and missing data. Features of the Second Edition include: Expanded coverage of interactions and the covariate-adjusted survival functions The use of the Worchester Heart Attack Study as the main modeling data set for illustrating discussed concepts and techniques New discussion of variable selection with multivariable fractional polynomials Further exploration of time-varying covariates, complex with examples Additional treatment of the exponential, Weibull, and log-logistic parametric regression models Increased emphasis on interpreting and using results as well as utilizing multiple imputation methods to analyze data with missing values New examples and exercises at the end of each chapter Analyses throughout the text are performed using Stata® Version 9, and an accompanying FTP site contains the data sets used in the book. Applied Survival Analysis, Second Edition is an ideal book for graduate-level courses in biostatistics, statistics, and epidemiologic methods. It also serves as a valuable reference for practitioners and researchers in any health-related field or for professionals in insurance and government.
546	1		_aContingut en anglès.
650		7	_aDemografia _xInvestigació _xMètodes estadístics _2lemac _9244
650		7	_aCiències de la salut _xMètodes estadístics _2lemac _912831
650		7	_aAnàlisi de regressió _xProcessament de dades _2lemac _9179
655		0	_2popin _9311 _aMEDICINA _fMEDICINE _iMEDICINA
655		7	_2popin _914269 _aANÁLISIS DE REGRESIÓN _fREGRESSION ANALYSIS _iANÀLISI DE REGRESSIÓ
655		7	_2popin _91110 _aMÉTODOS ESTADÍSTICOS _fSTATISTICAL METHODS _iMÈTODES ESTADÍSTICS
655		7	_2popin _914267 _aANÁLISIS BIOGRÁFICO _fEVENT HISTORY ANALYSIS _iANÀLISI BIOGRÀFICA
655		7	_91109 _aANÁLISIS DE DATOS _fDATA ANALYSIS _iANÀLISI DE DADES
700	1		_aLEMESHOW, Stanley _96814
700	1		_aMAY, Susanne _97183 _eaut.
901			_aRevisat
907			_a.b41053333 _b07-03-17 _c11-12-08 _d11-12-08 _em _fa _g- _heng _ixxu _j0 _k1
940			_aUPF
942			_2udc _cMO