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Statistical methods for survival data analysis / Elisa T. Lee, John Wenyu Wang.

By: Lee, Elisa T.
Contributor(s): Wang, John Wenyu.
Material type: materialTypeLabelBookCall no.: MED WA 2013 628658Series: Wiley series in probability and statistics: Publication: Hoboken, New Jersey : Wiley, [2013]Edition: Fourth edition.Description: xii, 484 p.ISBN: 9781118095027 (cloth); 1118095022 (cloth).Subject(s): Medicine -- Research -- Statistical methods | Failure time data analysis | Prognosis -- Statistical methods
Contents:
1 Introduction -- 1.1 Preliminaries -- 1.2 Censored Data -- 1.3 Scope of the Book -- 2 Functions of Survival Time -- 2.1 Definitions -- 2.2 Relationships of the Survival Functions -- 3 Examples of Survival Data Analysis -- 3.1 Example 3.1: Comparison of Two Treatments and Three Diets -- 3.2 Example 3.2: Comparison of Two Survival Patterns Using Life Tables -- 3.3 Example 3.3: Fitting Survival Distributions to Tumor-Free Times -- 3.4 Example 3.4: Comparing Survival of a Cohort with that of a General Population — Relative Survival -- 3.5 Example 3.5: Identification of Risk Factors for Incident Events -- 3.6 Example 3.6: Identification of Risk Factors for the Prevalence of Age-Related Macular Degeneration -- 3.7 Example 3.7: Identification of Significant Risk Factors for Incident Hypertension Using Related Data (Repeated Measurements) in a Longitudinal Study
4 Nonparametric Methods of Estimating Survival Functions -- 4.1 Product-Limit Estimates of Survivorship Function -- 4.2 N elson–Aalen Estimates of Survivorship Function -- 4.3 Life-Table Analysis -- 4.4 Relative Survival Rates -- 4.5 Standardized Rates and Ratios -- 5 Nonparametric Methods for Comparing Survival Distributions -- 5.1 Comparison of Two Survival Distributions -- 5.2 The Mantel and Haenszel Test -- 5.3 Comparison of K (K > 2) Samples -- 6 Some Well-Known Parametric Survival Distributions And Their Applications -- 6.1 Exponential Distribution -- 6.2 Weibull Distribution -- 6.3 Lognormal Distribution -- 6.4 Gamma, Generalized Gamma, and Extended Generalized Gamma Distributions -- 6.5 Log-Logistic Distribution -- 6.6 O ther Survival Distributions -- 7 Estimation Procedures for Parametric Survival Distributions Without Covariates
7.1 General Maximum Likelihood Estimation Procedure -- 7.2 Exponential Distribution -- 7.3 Weibull Distribution -- 7.4 Lognormal Distribution -- 7.5 The Extended Generalized Gamma Distribution -- 7.6 The Log-Logistic Distribution -- 7.7 Gompertz Distribution -- 7.8 Graphical Methods -- 8 Tests of Goodness-of-Fit and Distribution Selection -- 8.1 Goodness-of-Fit Test Statistics Based on Asymptotic Likelihood Inferences -- 8.2 Tests for Appropriateness of a Family of Distributions -- 8.3 Selection of a Distribution by Using BIC or AIC Procedure -- 8.4 Tests for a Specific Distribution with Known Parameters-- 8.5 Hollander and Proschan’s Test for Appropriateness of a Given Distribution with Known Parameters -- 9 Parametric Methods for Comparing Two Survival Distributions -- 9.1 Log-Likelihood Ratio Test for Comparing Two Survival Distributions
9.2 Comparison of Two Exponential Distributions -- 9.3 Comparison of Two Weibull Distributions -- 9.4 Comparison of Two Gamma Distributions -- 10 Parametric Methods for Regression Model Fitting and Identification of Prognostic Factors -- 10.1 Preliminary Examination of Data -- 10.2 General Structure of Parametric Regression Models and Their Asymptotic Likelihood Inference -- 10.3 Exponential AFT Model -- 10.4 Weibull AFT Model -- 10.5 Lognormal AFT Model -- 10.6 The Extended Generalized Gamma AFT Model -- 10.7 Log-Logistic AFT Model -- 10.8 O ther Parametric Regression Models -- 10.9 Model Selection Methods -- 11 Identification of Risk Factors Related to Survival Time: Cox Proportional Hazards Model -- 11.1 The Proportional Hazards Model -- 11.2 The Partial Likelihood Function -- 11.3 Identification of Significant Covariates
11.4 Estimation of the Survivorship Function with Covariates -- 11.5 Adequacy Assessment of the Proportional Hazards Model -- 12 Identification of Prognostic Factors Related to Survival Time: Non-Proportional Hazards Models -- 12.1 Models with Time-Dependent Covariates -- 12.2 Stratified Proportional Hazards Model -- 12.3 Competing Risks Model -- 12.4 Recurrent Event Models -- 12.5 Models for Related Observations -- 13 Identification of Risk Factors Related to Dichotomous and Polychotomous Outcomes -- 13.1 Univariate Analysis -- 13.2 Logistic and Conditional Logistic Regression Model for Dichotomous Outcomes -- 13.3 Models for Polychotomous Outcomes -- 13.4 Models for Related Observations.
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Includes bibliographical references and index.

1 Introduction -- 1.1 Preliminaries -- 1.2 Censored Data -- 1.3 Scope of the Book -- 2 Functions of Survival Time -- 2.1 Definitions -- 2.2 Relationships of the Survival Functions --
3 Examples of Survival Data Analysis -- 3.1 Example 3.1: Comparison of Two Treatments and Three Diets -- 3.2 Example 3.2: Comparison of Two Survival Patterns Using Life Tables --
3.3 Example 3.3: Fitting Survival Distributions to Tumor-Free Times -- 3.4 Example 3.4: Comparing Survival of a Cohort with that of a General Population — Relative Survival -- 3.5 Example 3.5: Identification of Risk Factors for Incident Events -- 3.6 Example 3.6: Identification of Risk Factors for the Prevalence of Age-Related Macular Degeneration -- 3.7 Example 3.7: Identification of Significant Risk Factors for Incident Hypertension Using Related Data (Repeated Measurements) in a Longitudinal Study

4 Nonparametric Methods of Estimating Survival Functions -- 4.1 Product-Limit Estimates of Survivorship Function -- 4.2 N elson–Aalen Estimates of Survivorship Function -- 4.3 Life-Table Analysis -- 4.4 Relative Survival Rates -- 4.5 Standardized Rates and Ratios -- 5 Nonparametric Methods for Comparing Survival Distributions --
5.1 Comparison of Two Survival Distributions -- 5.2 The Mantel and Haenszel Test -- 5.3 Comparison of K (K > 2) Samples -- 6 Some Well-Known Parametric Survival Distributions And Their Applications -- 6.1 Exponential Distribution -- 6.2 Weibull Distribution -- 6.3 Lognormal Distribution -- 6.4 Gamma, Generalized Gamma, and Extended Generalized Gamma Distributions -- 6.5 Log-Logistic Distribution -- 6.6 O ther Survival Distributions -- 7 Estimation Procedures for Parametric Survival Distributions Without Covariates

7.1 General Maximum Likelihood Estimation Procedure -- 7.2 Exponential Distribution -- 7.3 Weibull Distribution -- 7.4 Lognormal Distribution -- 7.5 The Extended Generalized Gamma Distribution -- 7.6 The Log-Logistic Distribution -- 7.7 Gompertz Distribution -- 7.8 Graphical Methods -- 8 Tests of Goodness-of-Fit and Distribution Selection -- 8.1 Goodness-of-Fit Test Statistics Based on Asymptotic Likelihood Inferences -- 8.2 Tests for Appropriateness of a Family of Distributions -- 8.3 Selection of a Distribution by Using BIC or AIC Procedure -- 8.4 Tests for a Specific Distribution with Known Parameters-- 8.5 Hollander and Proschan’s Test for Appropriateness of a Given Distribution with Known Parameters -- 9 Parametric Methods for Comparing Two Survival Distributions -- 9.1 Log-Likelihood Ratio Test for Comparing Two Survival Distributions

9.2 Comparison of Two Exponential Distributions -- 9.3 Comparison of Two Weibull Distributions -- 9.4 Comparison of Two Gamma Distributions -- 10 Parametric Methods for Regression Model Fitting and Identification of Prognostic Factors -- 10.1 Preliminary Examination of Data -- 10.2 General Structure of Parametric Regression Models and Their Asymptotic Likelihood Inference -- 10.3 Exponential AFT Model -- 10.4 Weibull AFT Model -- 10.5 Lognormal AFT Model -- 10.6 The Extended Generalized Gamma AFT Model -- 10.7 Log-Logistic AFT Model -- 10.8 O ther Parametric Regression Models -- 10.9 Model Selection Methods -- 11 Identification of Risk Factors Related to Survival Time: Cox Proportional Hazards Model -- 11.1 The Proportional Hazards Model -- 11.2 The Partial Likelihood Function -- 11.3 Identification of Significant Covariates

11.4 Estimation of the Survivorship Function with Covariates -- 11.5 Adequacy Assessment of the Proportional Hazards Model -- 12 Identification of Prognostic Factors Related to Survival Time: Non-Proportional Hazards Models -- 12.1 Models with Time-Dependent Covariates -- 12.2 Stratified Proportional Hazards Model -- 12.3 Competing Risks Model -- 12.4 Recurrent Event Models -- 12.5 Models for Related Observations -- 13 Identification of Risk Factors Related to Dichotomous and Polychotomous Outcomes -- 13.1 Univariate Analysis -- 13.2 Logistic and Conditional Logistic Regression Model for Dichotomous Outcomes -- 13.3 Models for Polychotomous Outcomes -- 13.4 Models for Related Observations.

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