Survival analysis in medicine and genetics
- Jialiang Li, Shuangge Ma.
- Boca Raton : CRC Press, 
- Physical description
- xvii, 363 pages : illustrations ; 25 cm.
- Chapman & Hall/CRC biostatistics series (Unnumbered)
Math & Statistics Library
|R853 .S7 L53 2013||Unknown|
- Includes bibliographical references (pages 327-360) and index.
- Introduction: Examples and Basic Principles Examples Design a Survival Study Description of Survival Distribution Censoring Mechanisms Analysis Trilogy: Estimation, Test, and Regression Estimation of Survival Distribution Two-Sample Comparison Regression Analysis Remarks Theoretic Notes Analysis of Interval Censored Data Definitions and Examples Parametric Modeling Nonparametric Modeling Two-Sample Comparison Semiparametric Modeling with Case I Interval Censored Data Semiparametric Modeling with Case II Interval Censored Data Discussions Appendix Special Modeling Methodology Nonparametric Regression Multivariate Survival Data Cure Rate Model Bayesian Analysis Theoretic Notes Diagnostic Medicine for Survival Analysis Statistics in Diagnostic Medicine Diagnostics for Survival Outcome under Diverse Censoring Patterns Diagnostics for Right Censored Data Theoretic Notes Survival Analysis with High-Dimensional Covariates Applications Identification of Marginal Association Multivariate Prediction Models Incorporating Hierarchical Structures Integrative Analysis Discussion Appendix Bibliography Index Exercises appear at the end of each chapter.
- (source: Nielsen Book Data)
- Publisher's Summary
- Using real data sets throughout, Survival Analysis in Medicine and Genetics introduces the latest methods for analyzing high-dimensional survival data. It provides thorough coverage of recent statistical developments in the medical and genetics fields. The text mainly addresses special concerns of the survival model. After covering the fundamentals, it discusses interval censoring, nonparametric and semiparametric hazard regression, multivariate survival data analysis, the sub-distribution method for competing risks data, the cure rate model, and Bayesian inference methods. The authors then focus on time-dependent diagnostic medicine and high-dimensional genetic data analysis. Many of the methods are illustrated with clinical examples. Emphasizing the applications of survival analysis techniques in genetics, this book presents a statistical framework for burgeoning research in this area and offers a set of established approaches for statistical analysis. It reveals a new way of looking at how predictors are associated with censored survival time and extracts novel statistical genetic methods for censored survival time outcome from the vast amount of research results in genomics.
(source: Nielsen Book Data)
- Publication date
- Chapman & Hall/CRC biostatistics series
- 9781439893111 (hardback)
- 143989311X (hardback)
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