ELISA T.LEE, JOHN WENYU WANG – STATISTICAL METHODS FOR SURVIVAL DATA ANALYSIS

Praise for the person. The third edition.

An easy to read introduction to survival analysis which covers the major concepts and techniques of the subject. Statistics in medical research.

It was updated and expanded to reflect the latest developments. Statistical methods for survival data analysis are in the fourth edition. A comprehensive introduction to the most commonly-used methods for analyzing survival data has been delivered. The Fourth Edition is a guide to statistical methods with applications in clinical trials, epidemiology, areas of business, and the social sciences. Special consideration is given to the study of survival data in the study of various fields in the book.

The most up-to-date information regarding software applications in the field is provided. Statistical methods for survival data analysis are in the fourth edition. Also includes:

• Marginal and random effect models for analyzing correlated censored or uncensored data
• Multiple types of two-sample and K-sample comparison analysis
• Updated treatment of parametric methods for regression model fitting with a new focus on accelerated failure time models
• Expanded coverage of the Cox proportional hazards model
• Exercises at the end of each chapter to deepen knowledge of the presented material

Statistical methods for analyzing survival data. It’s an ideal text for graduate-level courses on survival data analysis. The book is an excellent resource for researchers in every field in which the analysis of survival data plays a role.

There is a table of contents.

Preface xi

The introduction is 1

Preliminaries 1

The data was censored.

There is a scope of the book.

There are two functions of survival time.

There are 8 definitions.

The survival functions have relationships.

There are 16 exercises.

There are 3 examples of survival data analysis.

There is a comparison of two treatments and three diet.

Two survival patterns are compared using life tables.

3.3 is an example of fitting survival distributions.

Relative survival 30 is compared with survival of a cohort with a general population.

There are risk factors for incident events.

There are risk factors for the prevalence of age-related Macular Degeneration.

There are significant risk factors for hypertension identified using related data in a longitudinal study.

There are 54 exercises.

There are 4 nonparametric methods of estimating survival functions.

Product-Limit estimates of survival function

There are estimates of survivorship function.

The life-table analysis was 83.

The relative survival rates were 96.

There are 4.5 standardized rates and ratios.

There are 104 exercises.

There are 5 nonparametric methods for comparing survival distributions.

There is a comparison of two survival distributions.

The test is called The Mantel and Haenszel.

There is a comparison of K (K > 2) samples.

There are 130 exercises.

Parametric survival distribution applications are well-known.

The distribution is referred to as the exponential distribution.

There is a distribution by the name of Weibull.

Lognormal Distribution 142.

There are 6.4, Generalized, and Extended Generalized Gamma Distributions.

There is a Log-Logistic Distribution.

Survival Distributions 155

There are 159 exercises.

There are 7 Estimation Procedures for Parametric Survival Distributions.

The general maximum likelihood estimation procedure is 161.

There is a 7.2 exponential distribution.

There is a distribution by the name of Weibull Distribution 178.

Lognormal Distribution 180 is 7.4.

The distribution is extended generalized.

There is a log-logistic distribution.

Gompertz Distribution 185

There are 186 graphical methods.

There are exercises 203.

Goodness-of-fit and distribution selection are 8 tests.

The Goodness-of-Fit Test Statistics are based on the Asymptotic Likelihood Inferences.

There are tests for Appropriateness of a Family of Distributions.

BIC or AIC Procedure 216 are used for the selection of a distribution.

There are tests for a specific distribution.

Hollander and Proschan have a test for Appropriateness of a given distribution.

There are some exercises.

There are 9metric methods for comparing survival distributions.

The log-likelihood ratio test is used to compare survival distributions.

There is a comparison of two exponential distributions.

There is a comparison of two weibull distribution

Two Gamma Distributions 236 are compared.

There are 237 exercises.

There are 10metric methods for regression model fitting.

Preliminary examination of data

There is a general structure of regression models.

The AFT Model 246 is an exponential model.

There is a model of the AFT.

Lognormal AFT Model 258.

The AFT model is extended generalized.

There is a Log-Logistic AFT Model.

There are Parametric Regression Models.

There are model selection methods.

There are a number of exercises.

There are risk factors related to survival time.

The model is called the Proportional Hazards.

There is a partial likelihood function.

The identification of significant covariates.

The survival function is estimated with covariates.

The Proportional Hazards Model 317 has an Adequacy Assessment.

There are exercises.

There are prognostic factors related to survival time.

There are models with time- dependent coefficients.

Theified Proportional Hazards Model 346 is a model of Proportional Hazards.

Competing risks model 350

Recurrent event models 353.

There are models for related observations.

There are exercises.

There are 13 risk factors related to dichotomous and polychotomous outcomes.

There is a univariate analysis.

There is a Logistic and Conditional Logistic Regression Model for Dichotomous Outcomes.

There are models for Polychotomous Outcomes.

There are models for related observations.

The exercises are called exercises 440.

There is an appendix.

There are a number of references.

Index 477

Information about the author.

ELISA T. LEE is a PhD student. He is the Director of the Center for American Indian Health Research at the University of Oklahoma Health Sciences Center.

John Wang is a PhD student. The Center for American Indian Health Research is located at the University of Oklahoma Health Sciences Center.

Reviews

The fourth edition is a welcome addition to the available books on survival analysis. The addition of R software examples and the expanded sections on modelling are helpful. International Statistical Review. 1 October 2015.

John Wenyu Wang, Statistical Methods for Survival Data Analysis, is available for download.