Applied Survival Analysis

Introduces applied research areas and a number of real-life questions and examples with basic methods in nonparametric statistics, including the concept of censoring, which distinguishes survival analysis from other areas of statistics. 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 This concise, application-oriented text is designed to meet the needs of practitioners and students in applied fields in its coverage of major, updated methods in the analysis of survival data. Includes analysis of standardized mortality ratios, methods for proving attenuation of healthy worker effects, ordinal risk factors and other new areas of research. Timely and diverse case studies are presented, plus a complete data set on ESRD patients on hemodialysis. Moderate level of mathematics required.