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Survival and Event History Analysis. Wiley Reference Series in Biostatistics
John Wiley and Sons Ltd, October 2006, Pages: 550
A unique and invaluable reference resource for those working in survival analysis.
Survival analysis is concerned with studying the time between entry to a study and a subsequent event. Originally the analysis was concerned with time from treatment until death, hence the name, but survival analysis is applicable to many areas in addition to mortality, such as recidivism or the efficacy of drugs. The techniques can also be used in engineering and quality control (e.g. how long is a particular component likely to last?).
Arranged in an A-Z format, Survival and Event History Analysis edited by Niels Keiding and Per Kragh Andersen contains 96 articles written by over 60 distinguished authors. The articles are taken from the Encyclopedia of Biostatistics, 2nd Edition.
This book gives the reader a thorough grounding in the subject area and the extensive references at the end of each article provide a comprehensive source of information for further information in more depth.
List of Contributors.
List of Abbreviations and Acronyms.
Aalen's Additive Regression Model.
Accelerated Failure-time Models.
Additive Hazard Models.
Additive-Multiplicative Intensity Models.
Bayesian Approaches to Cure Rate Models.
Bayesian Model Selection in Survival Analysis.
Bayesian Survival Analysis.
Bootstrapping in Survival Analysis.
Case-Control Study, Nested.
Coarsening at Random.
Compliance and Survival Analysis.
Counting Process Methods in Survival Analysis.
Cox Regression Model.
Discrete Survival-time models.
Event History Analysis.
Expected Number of Deaths.
Expected Survival Curve.
Explained Variation Measures in Survival Analysis.
Goodness of Fit in Survival Analysis.
Grouped Survival Times.
Hazard Models Based on First-passage Time Distributions.
Hazard Ratio Estimator.
Historical Controls in Survival Analysis.
Influence Function in Survival Analysis.
Interim Analysis of Censored Data.
Inverse Probability Weighting in Survival Analysis.
Joint Modeling of Longitudinal and Event Time Data.
Kolmogorov-Smirnov and Cramer-Von Mises Tests in Survival Analysis.
Linear Rank Tests in Survival Analysis.
Marginal Models for Multivariate Survival Data.
Measurement Error in Survival Analysis.
Median Survival Time.
Multivariate Survival Analysis.
Nonparametric Maximum Likelihood.
Parametric Models in Survival Analysis.
Phase-type Distributions in Survival Analysis.
Poisson Regression in Epidemiology.
Prognostic Factors for Survival .
Proportional Hazards, Overview.
Quality of life and Survival Analysis.
Real Time Approach in Survival Analysis.
Relative Risk Modeling.
Residuals for Survival Analysis.
Sample Size Determination in Survival Analysis.
Smoothing Hazard Rates.
Structural Nested Failure Time Models.
Survival Analysis, Overview .
Survival Analysis, Software.
Survival Distributions and Their Characteristics.
Tied Survival Times .
Time Origin, Choice of.
Time to Pregnancy.
Total Time on Test.
Truncated Survival Times.
Type-specific Covariates in Survival Analysis.
"This volume is recommended to libraries, a welcome addition…" (Technometrics, August 2007)