Survival analysis with interval-censored data : a practical approach with examples in R, SAS and BUGS
Material type:
TextSeries: Chapman & Hall/CRC interdisciplinary statistics seriesPublication details: Boca Raton CRC 2018Description: xxxii, 584 pISBN: 9781420077476 (hardback : alk. paper)Subject(s): Survival Analysis | SoftwareDDC classification: 519.546 Summary: Survival Analysis with Interval-Censored Data: A Practical Approach with Examples in R, SAS, and BUGS provides the reader with a practical introduction into the analysis of interval-censored survival times. Although many theoretical developments have appeared in the last fifty years, interval censoring is often ignored in practice. Many are unaware of the impact of inappropriately dealing with interval censoring. In addition, the necessary software is at times difficult to trace. This book fills in the gap between theory and practice.
Features:
-Provides an overview of frequentist as well as Bayesian methods.
-Include a focus on practical aspects and applications.
-Extensively illustrates the methods with examples using R, SAS, and BUGS. Full programs are available on a supplementary website.
| Item type | Current library | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|
BK
|
Stack | 519.546 BOG/S (Browse shelf (Opens below)) | Available | 51081 |
Includes indexes.
Survival Analysis with Interval-Censored Data: A Practical Approach with Examples in R, SAS, and BUGS provides the reader with a practical introduction into the analysis of interval-censored survival times. Although many theoretical developments have appeared in the last fifty years, interval censoring is often ignored in practice. Many are unaware of the impact of inappropriately dealing with interval censoring. In addition, the necessary software is at times difficult to trace. This book fills in the gap between theory and practice.
Features:
-Provides an overview of frequentist as well as Bayesian methods.
-Include a focus on practical aspects and applications.
-Extensively illustrates the methods with examples using R, SAS, and BUGS. Full programs are available on a supplementary website.
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