Melania Pintilie

Competing Risks (eBook, PDF)

A Practical Perspective

• Format: PDF

Produktbeschreibung

The need to understand, interpret and analyse competing risk data is key to many areas of science, particularly medical research. There is a real need for a book that presents an overview of methodology used in the interpretation and analysis of competing risks, with a focus on practical applications to medical problems, and incorporating modern techniques. This book fills that need by presenting the most up-to-date methodology, in a way that can be readily understood, and applied, by the practitioner.

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Produktdetails

• Verlag: John Wiley & Sons
• Seitenzahl: 240
• Erscheinungstermin: 2. November 2006
• Englisch
• ISBN-13: 9780470870693
• Artikelnr.: 37299974

Autorenporträt

Melania Pintilie is the author of Competing Risks: A Practical Perspective, published by Wiley.

Inhaltsangabe

Preface. Acknowledgements. 1. Introduction. 1.1 Historical notes. 1.2
Defining competing risks. 1.3 Use of the Kaplan-Meier method in the
presence of competing risks. 1.4 Testing in the competing risk framework.
1.5 Sample size calculation. 1.6 Examples. 2. Survival - basic concepts.
2.1 Introduction. 2.2 Definitions and background formulae. 2.3 Estimation
and hypothesis testing. 2.4 Software for survival analysis. 2.5 Closing
remarks. 3. Competing risks - definitions. 3.1 Recognizing competing risks.
3.2 Two mathematical definitions. 3.3 Fundamental concepts. 3.4 Closing
remarks. 4. Descriptive methods for competing risks data. 4.1 Product-limit
estimator and competing risks. 4.2 Cumulative incidence function. 4.3
Software and examples. 4.4 Closing remarks. 5. Testing a covariate. 5.1
Introduction. 5.2 Testing a covariate. 5.3 Software and examples. 5.4
Closing remarks. 6. Modelling in the presence of competing risks. 6.1
Introduction. 6.2 Modelling the hazard of the cumulative incidence
function. 6.3 Cox model and competing risks. 6.4 Checking the model
assumptions. 6.5 Closing remarks. 7. Calculating the power in the presence
of competing risks. 7.1 Introduction. 7.2 Sample size calculation when
competing risks are not present. 7.3 Calculating power in the presence of
competing risks. 7.4 Examples. 7.5 Closing remarks. 8. Other issues in
competing risks. 8.1 Conditional probability function. 8.2 Comparing two
types of risk in the same population. 8.3 Identifiability and testing
independence. 8.4 Parametric modelling. 9. Food for thought. Problem 1:
Estimation of the probability of the event of interest. Problem 2: Testing
a covariate. Problem 3: Comparing the event of interest between two groups
when the competing risks are different for each group. Problem 4:
Information needed for sample size calculations. Problem 5: The effect of
the size of the incidence of competing risks on the coefficient obtained in
the model. Problem 6: The KLY test and the non-proportionality of hazards.
Problem 7: The KLY and Wilcoxon tests. A: Theoretical background. A.1
Nonparametric maximum likelihood estimation for the survivor function in
the discrete case. A.2 Confidence interval for survivor function. A.3 The
Variance for Gray's test. A.4 Derivation of the parameters for the
exponential latent failure time model. A.5 Likelihood of a mixture of
exponentials in the bivariate approach. B: Analysing competing risks data
using R and SAS. B.1 The R software and cmprsk package. B.2 Importing
datasets in SAS. B.3 Other programs written for R. B.4 SAS macros for
competing risk analysis. References. Index.

Rezensionen

"Will help statisticians and researchers understand the complexity of the competing-risks problem and to complete the analysis. I am glad to have it on my shelf." ( Technometrics , August 2008)
"...a concise introduction to the field of competing risks in survival analysis, especially useful for practitioners and researchers in the biostatistics field." ( Zentralblatt MATH , 2007)