Survival and Event History Analysis
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Survival and Event History Analysis by Niels Keiding
Book DescriptionA 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.
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Book DetailsISBN: 9780470058060
(252mm x 198mm x 37mm)
Imprint: John Wiley & Sons Ltd
Publisher: John Wiley and Sons Ltd
Publish Date: 6-Oct-2006
Country of Publication: United Kingdom
Books By Author Niels Keiding
Measurement Error, Hardback (March 2010)» View all books by Niels Keiding
Over the years, comprehensive strategies for treating measurement error in complex models and accounting for the use of extra data to estimate measurement error parameters have emerged. Focusing on both established and novel approaches, this title provides an overview of the main techniques and illustrates their application in various models.
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Author Biography - Niels Keiding
Niels Keiding and Per Andersen were Section Editors in Survival Analysis for both editions of the Encyclopedia of Biostatistics. They are extremely well known in their field and have written extensively, both books and research papers. They are based at the University of Copenhagen, and are both are on the advisory board for the journal Statistics in Medicine.
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