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Modelling survival data in medical research / David Collett.

By: Collett, D, 1952-.
Material type: TextTextSeries: Texts in statistical science: Publisher: Boca Raton, Fla. : Chapman & Hall/CRC, c2003Edition: 2nd ed.Description: 391 p. : ill. ; 24 cm.ISBN: 1584883251 (pbk. : alk. paper); 9781584883258.Subject(s): Survival analysis (Biometry) | Clinical trials -- Statistical methodsDDC classification: 610.727 Online resources: Publisher description | WorldCat Details | E-book Fulltext
Contents:
Table of contents Survival Analysis. Some Non-Parametric Procedures. Modelling Survival Data. Model Checking in the Cox Regression Model. Parametric Proportional Hazards Models. Accelerated Failure Time and other Parametric Models. Model Checking in Parametric Models. Time-Dependent Variables. Interval-Censored Survival Data. Sample Size Requirements for a Survival Study. Some Additional Topics. Computer Software for Survival Analysis. Appendices. References. Index of Examples. Index.
Summary: Summary: Survival analysis is an active field and many advances have emerged over the years. This book presents modelling techniques in survival data analysis, including developments in model checking, parametric models, time-dependent variables, and interval censored data. It focuses on the software sections on SAS.
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Includes bibliographical references (p. [371]-381) and indexes.

Table of contents Survival Analysis. Some Non-Parametric Procedures. Modelling Survival Data. Model Checking in the Cox Regression Model. Parametric Proportional Hazards Models. Accelerated Failure Time and other Parametric Models. Model Checking in Parametric Models. Time-Dependent Variables. Interval-Censored Survival Data. Sample Size Requirements for a Survival Study. Some Additional Topics. Computer Software for Survival Analysis. Appendices. References. Index of Examples. Index.

Summary:
Survival analysis is an active field and many advances have emerged over the years. This book presents modelling techniques in survival data analysis, including developments in model checking, parametric models, time-dependent variables, and interval censored data. It focuses on the software sections on SAS.

Applied Statistics

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