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Applied Survival Analysis: Regression Modeling of Time to Event Data …

This book places a unique emphasis on the practical and contemporary applications of regression modeling rather than the mathematical theory. It offers a clear and accessible presentation of modern modeling techniques supplemented with real-world examples and case studies. Key topics covered include: variable selection, identification of the scale of continuous covariates, the role of interactions in the model, assessment of fit and model assumptions, regression diagnostics, recurrent event models, frailty models, additive models, competing risk models, and missing data.

Applied Survival Analysis, Second Edition is an ideal book for graduate-level courses in biostatistics, statistics, and epidemiologic methods. It also serves as a valuable reference for practitioners and researchers in any health-related field or for professionals in insurance and government.


  • Survival Analysis — Part A.
  • CONCEPTS AND TERMINOLOGY IN SURVIVAL ANALYSIS.
  • A=B!
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David W. Hosmer is the coauthor of Applied Logistic Regression , published by Wiley.

Survival Analysis with R

Lemeshow has over thirty-five years of academic experience in the areas of regression, categorical data methods, and sampling methods. May has over twelve years of experience in providing statistical support for health-related research projects. Click to read or download. Researchers interested in the underlying theory will have to go elsewhere..

Time-To-Event Data Analysis

The authors are excellent teachers of the mathematics and application of survival data regression modeling. See All Customer Reviews.

Survival Analysis

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Temporarily Out of Stock Online Please check back later for updated availability. In addition, we may calculate summary measures of goodness-of-fit to support our efforts at model assessment. Methods for model assessment are discussed Stay ahead with the world's most comprehensive technology and business learning platform.

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