Statistical Methods for Survival Data Analysis

ISBN-10: 1118095022
ISBN-13: 9781118095027
Edition: 4th 2013
List price: $191.95 Buy it from $114.20
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Description: 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,  More...

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Book details

List price: $191.95
Edition: 4th
Copyright year: 2013
Publisher: John Wiley & Sons, Incorporated
Publication date: 9/27/2013
Binding: Hardcover
Pages: 512
Size: 6.50" wide x 9.50" long x 1.25" tall
Weight: 1.782
Language: English

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; real-world examples focused on survival data in the biomedical sciences; and more.

Preface
Introduction
Preliminaries
Censored Data
Scope of the Book
Functions of Survival Time
Definitions
Relationships of the Survival Functions
Exercises
Examples of Survival Data Analysis
Example 3.1: Comparison of Two Treatments and Three Diets
Example 3.2: Comparison of Two Survival Patterns Using Life Tables
Example 3.3: Fitting Survival Distributions to Tumor-Free Times
Example 3.4: Comparing Survival of a Cohort with that of a General Population - Relative Survival
Example 3.5: Identification of Risk Factors for Incident Events
Example 3.6: Identification of Risk Factors for the Prevalence of Age-Related Macular Degeneration
Example 3.7: Identification of Significant Risk Factors for Incident Hypertension Using Related Data (Repeated Measurements) in a Longitudinal Study
Exercises
Nonparametric Methods of Estimating Survival Functions
Product-Limit Estimates of Survivorship Function
Nelson-Aalen Estimates of Survivorship Function
Life-Table Analysis
Relative Survival Rates
Standardized Rates and Ratios
Exercises
Nonparametric Methods for Comparing Survival Distributions
Comparison of Two Survival Distributions
The Mantel and Haenszel Test
Comparison of K (K > 2) Samples
Exercises
Some Well-Known Parametric Survival Distributions And Their Applications
Exponential Distribution
Weibull Distribution
Lognormal Distribution
Gamma, Generalized Gamma, and Extended Generalized Gamma Distributions
Log-Logistic Distribution
Other Survival Distributions
Exercises
Estimation Procedures for Parametric Survival Distributions Without Covariates
General Maximum Likelihood Estimation Procedure
Exponential Distribution
Weibull Distribution
Lognormal Distribution
The Extended Generalized Gamma Distribution
The Log-Logistic Distribution
Gompertz Distribution
Graphical Methods
Exercises
Tests of Goodness-of-Fit and Distribution Selection
Goodness-of-Fit Test Statistics Based on Asymptotic Likelihood Inferences
Tests for Appropriateness of a Family of Distributions
Selection of a Distribution by Using BIC or AIC Procedure
Tests for a Specific Distribution with Known Parameters
Hollander and Proschan's Test for Appropriateness of a Given Distribution with Known Parameters
Exercises
Parametric Methods for Comparing Two Survival Distributions
Log-Likelihood Ratio Test for Comparing Two Survival Distributions
Comparison of Two Exponential Distributions
Comparison of Two Weibull Distributions
Comparison of Two Gamma Distributions
Exercises
Parametric Methods for Regression Model Fitting and Identification of Prognostic Factors
Preliminary Examination of Data
General Structure of Parametric Regression Models and Their Asymptotic Likelihood Inference
Exponential AFT Model
Weibull AFT Model
Lognormal AFT Model
The Extended Generalized Gamma AFT Model
Log-Logistic AFT Model
Other Parametric Regression Models
Model Selection Methods
Exercises
Identification of Risk Factors Related to Survival Time: Cox Proportional Hazards Model
The Proportional Hazards Model
The Partial Likelihood Function
Identification of Significant Covariates
Estimation of the Survivorship Function with Covariates
Adequacy Assessment of the Proportional Hazards Model
Exercises
Identification of Prognostic Factors Related to Survival Time: Non-Proportional Hazards Models
Models with Time-Dependent Covariates
Stratified Proportional Hazards Model
Competing Risks Model
Recurrent Event Models
Models for Related Observations
Exercises
Identification of Risk Factors Related to Dichotomous and Polychotomous Outcomes
Univariate Analysis
Logistic and Conditional Logistic Regression Models for Dichotomous Outcomes
Models for Polychotomous Outcomes
Models for Related Observations
Exercises
Appendix
References
Index

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