Pubbl/distr/stampa	London, : ISTE
Descrizione fisica	1 online resource (371 p.)
Disciplina	519.5/46 519.546
Altri autori (Persone)	HuberCatherine
Collana	ISTE
Soggetto topico	Failure time data analysis Survival analysis (Biometry)
ISBN	1-282-25388-3 9786613814531 0-470-61098-0 0-470-39356-4
Classificazione	QH 252
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Mathematical Methods in Survival Analysis, Reliability and Quality of Life; Contents; Preface; PART I; Chapter 1. Model Selection for Additive Regression in the Presence of Right-Censoring; 1.1. Introduction; 1.2. Assumptions on the model and the collection of approximation spaces; 1.2.1. Non-parametric regression model with censored data; 1.2.2. Description of the approximation spaces in the univariate case; 1.2.3. The particular multivariate setting of additive models; 1.3. The estimation method; 1.3.1. Transformation of the data; 1.3.2. The mean-square contrast 1.4. Main result for the adaptive mean-square estimator1.5. Practical implementation; 1.5.1. The algorithm; 1.5.2. Univariate examples; 1.5.3. Bivariate examples; 1.5.4. A trivariate example; 1.6. Bibliography; Chapter 2. Non-parametric Estimation of Conditional Probabilities, Means and Quantiles under Bias Sampling; 2.1. Introduction; 2.2. Non-parametric estimation of p; 2.3. Bias depending on the value of Y; 2.4. Bias due to truncation on X; 2.5. Truncation of a response variable in a non-parametric regression model; 2.6. Double censoring of a response variable in a non-parametric model 2.7. Other truncation and censoring of Y in a non-parametric model2.8. Observation by interval; 2.9. Bibliography; Chapter 3. Inference in Transformation Models for Arbitrarily Censored and Truncated Data; 3.1. Introduction; 3.2. Non-parametric estimation of the survival function S; 3.3. Semi-parametric estimation of the survival function S; 3.4. Simulations; 3.5. Bibliography; Chapter 4. Introduction of Within-area Risk Factor Distribution in Ecological Poisson Models; 4.1. Introduction; 4.2. Modeling framework; 4.2.1. Aggregated model; 4.2.2. Prior distributions; 4.3. Simulation framework 4.4. Results4.4.1. Strong association between relative risk and risk factor, correlated within-area means and variances (mean-dependent case); 4.4.2. Sensitivity to within-area distribution of the risk factor; 4.4.3. Application: leukemia and indoor radon exposure; 4.5. Discussion; 4.6. Bibliography; Chapter 5. Semi-Markov Processes and Usefulness in Medicine; 5.1. Introduction; 5.2. Methods; 5.2.1. Model description and notation; 5.2.2. Construction of health indicators; 5.3. An application to HIV control; 5.3.1. Context; 5.3.2. Estimation method 5.3.3. Results: new indicators of health state5.4. An application to breast cancer; 5.4.1. Context; 5.4.2. Age and stage-specific prevalence; 5.4.3. Estimation method; 5.4.4. Results: indicators of public health; 5.5. Discussion; 5.6. Bibliography; Chapter 6. Bivariate Cox Models; 6.1. Introduction; 6.2. A dependence model for duration data; 6.3. Some useful facts in bivariate dependence; 6.4. Coherence; 6.5. Covariates and estimation; 6.6. Application: regression of Spearman's rho on covariates; 6.7. Bibliography; Chapter 7. Non-parametric Estimation of a Class of Survival Functionals 7.1. Introduction
Record Nr.	UNINA-9910139469703321

Autore	Cleophas Ton J.
Edizione	[First edition.]
Pubbl/distr/stampa	Cham, Switzerland : , : Springer Nature Switzerland AG, , [2023]
Descrizione fisica	1 online resource (230 pages)
Disciplina	519.5
Soggetto topico	Failure time data analysis Regression analysis Survival analysis (Biometry)
ISBN	3-031-31632-0
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Intro -- Preface -- Contents -- Chapter 1: Regression Analysis -- 1.1 Introduction -- 1.2 History -- 1.3 Methodologies of Regression Analysis -- 1.3.1 Linear Regression -- 1.3.2 Logistic Regression -- 1.3.3 Cox Regression -- 1.4 Conclusion -- References -- Chapter 2: Cox Regressions -- 2.1 Introduction -- 2.2 History of Cox Regressions -- 2.3 Principles of Cox Regressions -- 2.4 Conclusion -- References -- Chapter 3: Accelerated Failure Time Models -- 3.1 Introduction -- 3.2 History of Failure Time Models -- 3.3 Methodology of Failure Time Models -- 3.4 Graphs of Successful Functions to Analyze Accelerated Failure Time Models -- 3.5 Conclusion -- References -- Chapter 4: Simple Dataset with Event as Outcome and Treatment as Predictor -- 4.1 Introduction -- 4.2 Data Example -- 4.3 Data Analysis in SPSS Statistical Software Version 29 -- 4.4 Cox Regression -- 4.5 Accelerated Failure Time with Weibull Distribution -- 4.6 Accelerated Failure Time Model with Exponential Distribution -- 4.7 Accelerated Failure Time Model with Log Normal Distribution -- 4.8 Accelerated Failure Time Model with Log Logistic Distribution -- 4.9 Conclusion -- References -- Chapter 5: Simple Dataset with Death as Outcome and Treatment Modality, Cholesterol, and Age as Predictors -- 5.1 Introduction -- 5.2 Data Example -- 5.3 Data Analysis in SPSS Statistical Software Version 29 -- 5.4 Three Predictors Cox Regression -- 5.5 Three Predictors Accelerated Failure Time (AFT) with Weibull Distribution -- 5.6 Three Predictors Accelerated Failure Time Model with Exponential Distribution -- 5.7 Three Predictors Accelerated Failure Time with Log Normal Distribution -- 5.8 Three Predictors Accelerated Failure Time with Log Logistic Distribution -- 5.9 Conclusion -- References -- Chapter 6: Glioma Brain Cancer -- 6.1 Introduction -- 6.2 Data Example. 6.3 Data Analysis in SPSS Statistical Software Version 29 -- 6.4 Cox Regression -- 6.5 Accelerated Failure Time (AFT) Model with Weibull Distribution -- 6.6 The Accelerated Failure Time (AFT) with Exponential Distribution -- 6.7 Accelerated Failure Time (AFT) with Log Normal Distribution -- 6.8 Accelerated Failure Time with Log-logistic Distribution -- 6.9 Conclusion -- References -- Chapter 7: Linoleic Acid for Colonic Carcinoma -- 7.1 Introduction -- 7.2 Data Example -- 7.3 Data Analysis in SPSS Statistical Software Version 29 -- 7.4 Cox Regression -- 7.5 Accelerated Failure Time (AFT) with Weibull Distribution -- 7.6 Accelerated Failure Time (AFT) with Exponential Distribution -- 7.7 Accelerated Failure Time (AFT) with Log Normal Distribution -- 7.8 Accelerated Failure Time (AFT) with Log Logistic Distribution -- 7.9 Conclusion -- References -- Chapter 8: The Effect on Survival of Maintained Chemotherapy with Acute Myelogenous Leucemia -- 8.1 Introduction -- 8.2 Data Example -- 8.3 Data Analysis in SPSS Statistical Software Version 29 -- 8.4 Cox Regression -- 8.5 Accelerated Failure Time (AFT) with Weibull Distribution -- 8.6 Accelerated Failure Time (AFT) with Exponential Distribution -- 8.7 Accelerated Failure Time (AFT) with Log Normal Distribution -- 8.8 Accelerated Failure Time (AFT) with Log Logistic Distribution -- 8.9 Conclusion -- References -- Chapter 9: Eighty Four Month Parallel Group Mortality Study -- 9.1 Introduction -- 9.2 Data Example -- 9.3 Data Analysis in SPSS Statistical Software Version 29 -- 9.4 Cox Regression -- 9.5 Accelerated Failure Time (AFT) Model with the Weibull Distribution -- 9.6 Accelerated Failure Time (AFT) Model with the Exponential Distribution -- 9.7 Accelerated Failure Time (AFT) Model with the Log Normal Distribution -- 9.8 Accelerated Failure Time (AFT) Model with Log Logistic Distribution. 9.9 Conclusion -- References -- Chapter 10: The Effect on Survival from Stages 1 and 2 Histiocytic Lymphoma -- 10.1 Introduction -- 10.2 Data Example -- 10.3 Data Analysis Using SPSS Statistical Software Version 29 -- 10.4 Cox Regression -- 10.5 Accelerated Failure Time (AFT) with Weibull Distribution -- 10.6 Accelerated Failure Time (AFT) with Exponential Distribution -- 10.7 Accelerated Failure Time (AFT) with Log Normal Distribution -- 10.8 Accelerated Failure Time (AFT) with Log Logistic Distribution -- 10.9 Conclusion -- References -- Chapter 11: Survival of 64 Lymphoma Patients with or Without B Symptoms -- 11.1 Introduction -- 11.2 Data Example -- 11.3 Data Analysis in SPSS Statistical Software Version 29 -- 11.4 Cox Regression -- 11.5 Accelerated Failure Time (AFT) Model with Weibull Distribution -- 11.6 Accelerated Failure Time (AFT) Model with Exponential Distribution -- 11.7 Accelerated Failure Time (AFT) Model with Log Normal Distribution -- 11.8 Accelerated Failure Time (AFT) Model with Log Logistic Distribution -- 11.9 Conclusion -- References -- Chapter 12: Effect on Time-to-Event of Group Membership -- 12.1 Introduction -- 12.2 Data Example -- 12.3 Data Analysis Using SPSS Statistical Software Version 29 -- 12.4 Cox Regression -- 12.5 Accelerated Failure Time (AFT) Model with Weibull Distribution -- 12.6 Accelerated Failure Time (AFT) with Exponential Distribution -- 12.7 Accelerated Failure Time (AFT) with Log Normal Distribution -- 12.8 Accelerated Failure Time (AFT) with Log Logistic Distribution -- 12.9 Conclusion -- References -- Chapter 13: The Effect on Survival of Group Membership -- 13.1 Introduction -- 13.2 Data Example -- 13.3 Data Analysis Using SPSS Statistical Software Version 29 -- 13.4 Cox Regression -- 13.5 Accelerated Failure Time (AFT) Models with Weibull Distribution. 13.6 Accelerated Failure Time (AFT) Models with Exponential Distribution -- 13.7 Accelerated Failure Time (AFT) Model with Log Normal Distribution -- 13.8 Accelerated Failure Time (AFT) Model with Log Logistics Distribution -- 13.9 Conclusion -- References -- Chapter 14: Deaths from Carcinoma After Exposure to Carcinogens in Rats -- 14.1 Introduction -- 14.2 Data Example -- 14.3 Data Analysis Using SPSS Statistical Software Version 29 -- 14.4 Cox Regression -- 14.5 Accelerated Failure Time (AFT) Model with Weibull Distribution -- 14.6 Accelerated Failure Time (AFT) Model with Exponential Distribution -- 14.7 Accelerated Failure Time (AFT) Model with Log Normal Distribution -- 14.8 Accelerated Failure Time (AFT) Model with Log Logistics Distribution -- 14.9 Conclusion -- References -- Chapter 15: Effect of Group Membership on Survival -- 15.1 Introduction -- 15.2 Data Example -- 15.3 Data Analysis Using SPSS Statistical Software Version 29 -- 15.4 Cox Regression -- 15.5 Accelerated Failure Time (AFT) Models with Weibull Distribution -- 15.6 Accelerated Failure Time (AFT) Model with Exponential Distribution -- 15.7 Accelerated Failure Time (AFT) Model with Log Normal Distribution -- 15.8 Accelerated Failure Time (AFT) Model with Log Logistics Distribution -- 15.9 Conclusion -- References -- Chapter 16: Multiple Variables Regression Study of 2421 Stroke Patients Assessed for Time to Second Stroke -- 16.1 Introduction and Data Example -- 16.2 Data Analysis in SPSS Statistical Software Version 29 -- 16.3 Cox Regression -- 16.4 Accelerated Failure Time (AFT) with Weibull Distribution -- 16.5 Accelerated Failure Time (AFT) with Exponential Distribution -- 16.6 Accelerated Failure Time (AFT) with Log Normal Distribution -- 16.7 Accelerated Failure Time (AFT) with Log Logistic Distribution -- 16.8 Conclusion -- References. Chapter 17: Hypothesized 55 Patient Study of Effect of Treatment Modality on Survival -- 17.1 Introduction -- 17.2 Data Example -- 17.3 Data Analysis Using SPSS Statistical Software Version 29 -- 17.4 Cox Regression -- 17.5 Accelerated Failure Time (AFT) with Weibull's Distribution -- 17.6 Accelerated Failure Time (AFT) with Exponential Distribution -- 17.7 Acccelerated Failure Time (AFT) with Log Normal Distribution -- 17.8 Accelerated Failure Time (AFT) with Log Logistic Distribution -- 17.9 Conclusion -- References -- Chapter 18: One Year Follow-Up Study with Many Censored Patients -- 18.1 Introduction -- 18.2 Data Example -- 18.3 Data Analysis Using SPSS Statistical Software Version 29 -- 18.4 Cox Regression -- 18.5 Accelerated Failure Time (AFT) with Weibull Distribution -- 18.6 Accelerated Failure Time (AFT) Model with Exponential Distribution -- 18.7 Accelerated Failure Time (AFT) Model with Log Normal Distribution -- 18.8 Accelerated Failure Time (AFT) Model with Log Logistics Distribution -- 18.9 Conclusion -- References -- Chapter 19: Alcohol Relapse After Detox Program Treated with or Without a Personal Coach -- 19.1 Introduction -- 19.2 Data Example -- 19.3 Data Analysis Using SPSS Statistical Software Version 29 -- 19.4 Cox Regression -- 19.5 Accelerated Failure Time (AFT) Models with Weibull Distribution -- 19.6 Accelerated Failure Times (AFT) Model with Exponential Distribution -- 19.7 Accelerated Failure Time (AFT) Model with Log Normal Distribution -- 19.8 Accelerated Failure Times (AFT) Model with Log Logistics Distribution -- 19.9 Conclusion -- References -- Chapter 20: Alcohol Relapse After Detox Program with 3 Predictors -- 20.1 Introduction -- 20.2 Data Example -- 20.3 Data Analysis Using SPSS Statistical Software Version 29 -- 20.4 Cox Regression -- 20.5 Accelerated Failure Time (AFT) Model with Weibull Distribution. 20.6 Accelerated Failure Time Model with Exponential Distribution.
Record Nr.	UNINA-9910728386303321

Autore	Kalbfleisch J. D.
Edizione	[Second edition.]
Pubbl/distr/stampa	Hoboken, N.J. : , : J. Wiley, , [2002]
Descrizione fisica	1 online resource (464 pages) : illustrations
Disciplina	519.287 519.5
Collana	Wiley series in probability and statistics
Soggetto topico	Failure time data analysis Survival analysis (Biometry) Regression analysis
Soggetto genere / forma	Electronic books.
ISBN	1-282-24269-5 9786613813817 1-118-03298-5 1-118-03123-7
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	The Statistical Analysis of Failure Time Data; Contents; Preface; 1. Introduction; 1.1 Failure Time Data; 1.2 Failure Time Distributions; 1.3 Time Origins, Censoring, and Truncation; 1.4 Estimation of the Survivor Function; 1.5 Comparison of Survival Curves; 1.6 Generalizations to Accommodate Delayed Entry; 1.7 Counting Process Notation; Bibliographic Notes; Exercises and Complements; 2. Failure Time Models; 2.1 Introduction; 2.2 Some Continuous Parametric Failure Time Models; 2.3 Regression Models; 2.4 Discrete Failure Time Models; Bibliographic Notes; Exercises and Complements 3. Inference in Parametric Models and Related Topics3.1 Introduction; 3.2 Censoring Mechanisms; 3.3 Censored Samples from an Exponential Distribution; 3.4 Large-Sample Likelihood Theory; 3.5 Exponential Regression; 3.6 Estimation in Log-Linear Regression Models; 3.7 Illustrations in More Complex Data Sets; 3.8 Discrimination Among Parametric Models; 3.9 Inference with Interval Censoring; 3.10 Discussion; Bibliographic Notes; Exercises and Complements; 4. Relative Risk (Cox) Regression Models; 4.1 Introduction; 4.2 Estimation of β; 4.3 Estimation of the Baseline Hazard or Survivor Function 4.4 Inclusion of Strata4.5 Illustrations; 4.6 Counting Process Formulas; 4.7 Related Topics on the Cox Model; 4.8 Sampling from Discrete Models; Bibliographic Notes; Exercises and Complements; 5. Counting Processes and Asymptotic Theory; 5.1 Introduction; 5.2 Counting Processes and Intensity Functions; 5.3 Martingales; 5.4 Vector-Valued Martingales; 5.5 Martingale Central Limit Theorem; 5.6 Asymptotics Associated with Chapter 1; 5.7 Asymptotic Results for the Cox Model; 5.8 Asymptotic Results for Parametric Models; 5.9 Efficiency of the Cox Model Estimator; 5.10 Partial Likelihood Filtration Bibliographic NotesExercises and Complements; 6. Likelihood Construction and Further Results; 6.1 Introduction; 6.2 Likelihood Construction in Parametric Models; 6.3 Time-Dependent Covariates and Further Remarks on Likelihood Construction; 6.4 Time Dependence in the Relative Risk Model; 6.5 Nonnested Conditioning Events; 6.6 Residuals and Model Checking for the Cox Model; Bibliographic Notes; Exercises and Complements; 7. Rank Regression and the Accelerated Failure Time Model; 7.1 Introduction; 7.2 Linear Rank Tests; 7.3 Development and Properties of Linear Rank Tests 7.4 Estimation in the Accelerated Failure Time Model7.5 Some Related Regression Models; Bibliographic Notes; Exercises and Complements; 8. Competing Risks and Multistate Models; 8.1 Introduction; 8.2 Competing Risks; 8.3 Life-History Processes; Bibliographic Notes; Exercises and Complements; 9. Modeling and Analysis of Recurrent Event Data; 9.1 Introduction; 9.2 Intensity Processes for Recurrent Events; 9.3 Overall Intensity Process Modeling and Estimation; 9.4 Mean Process Modeling and Estimation; 9.5 Conditioning on Aspects of the Counting Process History; Bibliographic Notes Exercises and Complements
Record Nr.	UNINA-9910139191003321

Autore	Lee Elisa T
Edizione	[Fourth edition.]
Pubbl/distr/stampa	Hoboken, New Jersey : , : Wiley, a John Wiley & Sons, Inc., , [2013]
Descrizione fisica	1 online resource (508 pages) : illustrations
Disciplina	610.72/7
Altri autori (Persone)	WangJohn Wenyu
Collana	Wiley series in probability and statistics
Soggetto topico	Medicine - Research - Statistical methods Failure time data analysis Prognosis - Statistical methods
Soggetto genere / forma	Electronic books.
ISBN	1-118-59305-7 1-118-71615-9 1-118-59311-1
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Record Nr.	UNINA-9910452811803321

Autore	Lawless J. F (Jerald F.), <1944->
Edizione	[Second edition]
Pubbl/distr/stampa	Hoboken, N.J., : Wiley-Interscience, c2003
Descrizione fisica	1 online resource (662 pages)
Disciplina	519.5
Collana	Wiley series in probability and statistics
Soggetto topico	Failure time data analysis Survival analysis (Biometry)
ISBN	1-282-25336-0 9786613814012 1-118-03300-0 1-118-03125-3
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Record Nr.	UNINA-9910138874603321