Advances in survival analysis /

• Άλλοι συγγραφείς: Balakrishnan, N., 1956- (Επιμελητής έκδοσης), Rao, C. Radhakrishna (Calyampudi Radhakrishna), 1920- (Επιμελητής έκδοσης)
• Μορφή: Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Amsterdam ; Boston : Elsevier North-Holland, 2004.
• Έκδοση: 1st ed.
• Σειρά: Handbook of statistics (Amsterdam, Netherlands) ; v. 23.
• Θέματα: Failure time data analysis.; Survival Analysis.; MATHEMATICS > Probability & Statistics > General.; Overlevingsanalyse.; Analyse des temps entre défaillances.; Analyse de survie (Statistique); Modèle statistique.; Statistik; Ereignisdatenanalyse; Industrie; Electronic books.; Aufsatzsammlung.

 The book covers all important topics in the area of Survival Analysis. Each topic has been covered by one or more chapters written by internationally renowned experts. Each chapter provides a comprehensive and up-to-date review of the topic. Several new illustrative examples have been used to demonstrate the methodologies developed. The book also includes an exhaustive list of important references in the area of Survival Analysis. Includes up-to-date reviews on many important topics. Chapters written by many internationally renowned experts. Some Chapters provide completely new methodologies and analyses. Includes some new data and methods of analyzing them. 

 Cover -- Table of Contents -- Preface -- Contributors -- PART I: GENERAL METHODOLOGY -- Chapter 1. Evaluation of the Performance of Survival Analysis Models: Discrimination and Calibration Measures -- 1. Introduction -- 2. Discrimination index -- 3. Calibration measures in survival analysis -- Appendix A -- References -- Chapter 2. Discretizing a Continuous Covariate in Survival Studies -- 1. Introduction -- 2. Techniques based on the Cox model with a single covariate -- 3. Extensions of Contal and O'Quigley's approach -- 4. Discussion -- Acknowledgements -- References -- Chapter 3. On Comparison of Two Classification Methods with Survival Endpoints -- 1. Introduction -- 2. Degree of separation index -- 3. Estimation and inference procedures -- 4. Distribution property of test statistics under the null hypothesis -- 5. Application examples -- 6. Discussion and conclusion -- Acknowledgement -- References -- Chapter 4. Time Varying Effects in Survival Analysis -- 1. Time varying effects in survival analysis -- 2. Estimation for proportional or additive models -- 3. Testing in proportional and additive hazards models -- 4. Survival with malignant melanoma -- 5. Discussion -- Acknowledgement -- References -- Chapter 5. Kaplan-Meier Integrals -- 1. Introduction -- 2. The SLLN -- 3. The CLT -- 4. Bias -- 5. The jackknife -- 6. Censored correlation and regression -- 7. Conclusions -- References -- PART II: CENSORED DATA AND INFERENCE -- Chapter 6. Statistical Analysis of Doubly Interval-Censored Failure Time Data -- 1. Introduction -- 2. Nonparametric estimation of a distribution function -- 3. Semiparametric regression analysis -- 4. Nonparametric comparison of survival functions -- 5. Discussion and future researches -- References -- Chapter 7. The Missing Censoring-Indicator Model of Random Censorship -- 1. Introduction -- 2. Overview of the estimators of a survival function -- 3. Semiparametric estimation in the MCI model -- 4. Conclusion -- Acknowledgement -- References -- Chapter 8. Estimation of the Bivariate Survival Function with Generalized Bivariate Right Censored Data Structures -- 1. Introduction -- 2. Modeling the censoring mechanism -- 3. Constructing an initial mapping from full data estimating functions to observed data estimating functions -- 4. Generalized Dabrowska's estimator -- 5. Orthogonalized estimating function and corresponding estimator -- 6. Simulations -- 7. Discussion -- Appendix A -- References -- Chapter 9. Estimation of Semi-Markov Models with Right-Censored Data -- 1. Introduction -- 2. Definition of the estimators -- 3. Asymptotic distribution of the estimators -- 4. Generalization to models with covariates -- 5. Discussion -- References -- PART III: TRUNCATED DATA AND INFERENCE -- Chapter 10. Nonparametric Bivariate Estimation with Randomly Truncated Observations -- 1. Introduction -- 2. Estimation of the bivariate distribution function -- 3. Estimation of bivariate hazard -- 4. Biv.