Applied Survival Analysis

Major, updated methods of survival data analysis in one concise volume Applied Survival Analysis provides the foundation for understanding various analytical procedures and the relationships among these different methods. The book is application–oriented yet also serves as a superb single–volume reference. It develops new areas of research, such as the analysis of clustered survival data, and presents cohort and case–control studies, including healthy worker effects and applications to receiver operating characteristic (ROC) curves. Written for graduate students in biostatistics, epidemiology, and environmental health, as well as for professional statisticians and biomedical researchers, Applied Survival Analysis:
∗ Features applied research areas, real–life examples with detailed descriptions, and exercises
∗ Provides equations, derivations, and proofs that require only simple algebra and elementary calculus
∗ Integrates a discussion on implementation in the form of algorithms and sample SAS commands
∗ Includes three appendices that contain real–life data sets on end–stage renal diseases and paired survival data, including a complete data set on ESRD patients on hemodialysis

Spis treści:
Basic Concepts in Survival Analysis.
Estimation of Functions and Parameters.
Comparison of Survival Distributions.
Correlation and Regression Analyses.
Appendices.
References.
Index.

Nota biograficzna:
CHAP T. LE, PhD, is Professor and Director of Biostatistics at the University of Minnesota′s Cancer Center and Otitis Media Research Center. Dr. Le′s many works on biostatistics include Health and Numbers: Basic Biostatistical Methods (Wiley), coauthored with James R. Boen.

Okładka tylna:
Major, updated methods of survival data analysis in one concise volume Applied Survival Analysis provides the foundation for understandi ng various analytical procedures and the relationships among these different methods. The book is application–oriented yet also serves as a superb single–volume reference. It develops new areas of research, such as the analysis of clustered survival data, and presents cohort and case–control studies, including healthy worker effects and applications to receiver operating characteristic (ROC) curves. Written for graduate students in biostatistics, epidemiology, and environmental health, as well as for professional statisticians and biomedical researchers, Applied Survival Analysis:
∗ Features applied research areas, real–life examples with detailed descriptions, and exercises
∗ Provides equations, derivations, and proofs that require only simple algebra and elementary calculus
∗ Integrates a discussion on implementation in the form of algorithms and sample SAS commands
∗ Includes three appendices that contain real–life data sets on end–stage renal diseases and paired survival data, including a complete data set on ESRD patients on hemodialysis