Statistical methods for survival data analysis
 Responsibility
 Elisa T. Lee, John Wenyu Wang.
 Edition
 Fourth edition.
 Publication
 Hoboken, New Jersey : Wiley, [2013]
 Physical description
 xii, 484 pages : illustrations ; 24 cm.
 Series
 Wiley series in probability and statistics.
Access
Available online
Science Library (Li and Ma)
Stacks
Call number  Status 

R853 .S7 L43 2013  Unknown 
More options
Creators/Contributors
 Author/Creator
 Lee, Elisa T.
 Contributor
 Wang, John Wenyu.
Contents/Summary
 Bibliography
 Includes bibliographical references (pages 466476) and index.
 Contents

 Preface xi 1 Introduction 1 1.1 Preliminaries 1 1.2 Censored Data 2 1.3 Scope of the Book 5 2 Functions of Survival Time 8 2.1 Definitions 8 2.2 Relationships of the Survival Functions 15 Exercises 16 3 Examples of Survival Data Analysis 19 3.1 Example 3.1: Comparison of Two Treatments and Three Diets19 3.2 Example 3.2: Comparison of Two Survival Patterns Using LifeTables 26 3.3 Example 3.3: Fitting Survival Distributions to TumorFree Times28 3.4 Example 3.4: Comparing Survival of a Cohort with that of aGeneral Population Relative Survival 30 3.5 Example 3.5: Identification of Risk Factors for Incident Events33 3.6 Example 3.6: Identification of Risk Factors for the Prevalenceof AgeRelated Macular Degeneration 38 3.7 Example 3.7: Identification of Significant Risk Factors forIncident Hypertension Using Related Data (Repeated Measurements) ina Longitudinal Study 46 Exercises 54 4 Nonparametric Methods of Estimating Survival Functions68 4.1 ProductLimit Estimates of Survivorship Function 69 4.2 N elson Aalen Estimates of Survivorship Function 82 4.3 LifeTable Analysis 83 4.4 Relative Survival Rates 96 4.5 Standardized Rates and Ratios 98 Exercises 104 5 Nonparametric Methods for Comparing Survival Distributions108 5.1 Comparison of Two Survival Distributions 108 5.2 The Mantel and Haenszel Test 123 5.3 Comparison of K (K > 2) Samples 128 Exercises 130 6 Some WellKnown Parametric Survival Distributions And TheirApplications 133 6.1 Exponential Distribution 133 6.2 Weibull Distribution 138 6.3 Lognormal Distribution 143 6.4 Gamma, Generalized Gamma, and Extended Generalized GammaDistributions 148 6.5 LogLogistic Distribution 153 6.6 O ther Survival Distributions 155 Exercises 159 7 Estimation Procedures for Parametric Survival DistributionsWithout Covariates 161 7.1 General Maximum Likelihood Estimation Procedure 161 7.2 Exponential Distribution 165 7.3 Weibull Distribution 178 7.4 Lognormal Distribution 180 7.5 The Extended Generalized Gamma Distribution 183 7.6 The LogLogistic Distribution 184 7.7 Gompertz Distribution 185 7.8 Graphical Methods 186 Exercises 203 8 Tests of GoodnessofFit and Distribution Selection206 8.1 GoodnessofFit Test Statistics Based on Asymptotic LikelihoodInferences 207 8.2 Tests for Appropriateness of a Family of Distributions210 8.3 Selection of a Distribution by Using BIC or AIC Procedure216 8.4 Tests for a Specific Distribution with Known Parameters217 8.5 Hollander and Proschan s Test for Appropriateness of aGiven Distribution with Known Parameters 220 Exercises 224 9 Parametric Methods for Comparing Two Survival Distributions226 9.1 LogLikelihood Ratio Test for Comparing Two SurvivalDistributions 226 9.2 Comparison of Two Exponential Distributions 229 9.3 Comparison of Two Weibull Distributions 234 9.4 Comparison of Two Gamma Distributions 236 Exercises 237 10 Parametric Methods for Regression Model Fitting andIdentification of Prognostic Factors 239 10.1 Preliminary Examination of Data 240 10.2 General Structure of Parametric Regression Models and TheirAsymptotic Likelihood Inference 242 10.3 Exponential AFT Model 246 10.4 Weibull AFT Model 255 10.5 Lognormal AFT Model 258 10.6 The Extended Generalized Gamma AFT Model 261 10.7 LogLogistic AFT Model 264 10.8 O ther Parametric Regression Models 268 10.9 Model Selection Methods 270 Exercises 279 11 Identification of Risk Factors Related to Survival Time: CoxProportional Hazards Model 282 11.1 The Proportional Hazards Model 282 11.2 The Partial Likelihood Function 285 11.3 Identification of Significant Covariates 302 11.4 Estimation of the Survivorship Function with Covariates309 11.5 Adequacy Assessment of the Proportional Hazards Model317 Exercises 334 12 Identification of Prognostic Factors Related to SurvivalTime: NonProportional Hazards Models 337 12.1 Models with TimeDependent Covariates 337 12.2 Stratified Proportional Hazards Model 346 12.3 Competing Risks Model 350 12.4 Recurrent Event Models 353 12.5 Models for Related Observations 370 Exercises 382 13 Identification of Risk Factors Related to Dichotomous andPolychotomous Outcomes 384 13.1 Univariate Analysis 385 13.2 Logistic and Conditional Logistic Regression Model forDichotomous Outcomes 392 13.3 Models for Polychotomous Outcomes 421 13.4 Models for Related Observations 432 Exercises 440 Appendix 443 References 466 Index 477.
 (source: Nielsen Book Data)9781118095027 20160612
 Publisher's Summary
 Upgraded to reflect the latest research and software applications on the topic, this new edition continues to provide a comprehensive introduction to the statistical methods for analyzing survival data. It features a wealth of new material, including coverage of marginal and random effect models for analyzing correlated censored or uncensored data as well as multiple comparisons in the comparison of K samples. It also offers expanded coverage of the Cox proportional hazards model; realworld examples focused on survival data in the biomedical sciences; and more.
(source: Nielsen Book Data)9781118095027 20160612
Subjects
Bibliographic information
 Publication date
 2013
 Series
 Wiley series in probability and statistics
 ISBN
 9781118095027 (hbk.)
 1118095022 (hbk.)