Critically acclaimed and resoundingly popular in its first edition, Modelling Survival Data in Medical Research has been thoroughly revised and updated to reflect the many developments and advances--particularly in software--made in the field over the last 10 years. Now, more than ever, it provides an outstanding text for upper-level and graduate courses in survival analysis, biostatistics, and time-to-event analysis.The treatment begins with an introduction to survival analysis and a description of four studies that lead to survival data. Subsequent chapters then use those data sets and others to illustrate the various analytical techniques applicable to such data, including the Cox regression model, the Weibull proportional hazards model, and others. This edition features a more detailed treatment of topics such as parametric models, accelerated failure time models, and analysis of interval-censored data. The author also focuses the software section on the use of SAS, summarising the methods used by the software to generate its output and examining that output in detail. Profusely illustrated with examples and written in the author's trademark, easy-to-follow style, Modelling Survival Data in Medical Research, Second Edition is a thorough, practical guide to survival analysis that reflects current statistical practices.
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Editorial Reviews
Review
Collett has succeeded admirably in updating the first edition of his book … [This book] has numerous, carefully worked, real-data examples. There is enough new material in the second edition to justify its purchase by someone who already owns the first edition.
—Journal of the American Statistical Association, Sept. 2004, Vol. 99, No. 467
this text is a fine example of technical writing and remains highly recommended for both students and researchers requiring an introduction to survival analysis in a medical context.
—Journal of the Royal Statistical Society, Issue 167 (4)
… a well written practical guide with a demonstration of SAS software to perform survival analysis. … It can be used as a textbook in a graduate-level survival analysis course … .
—Journal of Statistical Computation & Simulation, Vol. 74, No. 5, May 2004
It is thorough and authoritative, covers all essential theory and contains many practical tips.
—Journal of the Royal Statistical Society, Vol. 157
Praise for the First Edition:
… a useful book that has particular merit for the applied statistician. Chapters 1-6 and 11 alone supply a wonderful introduction to survival analysis. The mathematical statistician unfamiliar with survival analysis who desires to become quickly abreast will also gain much from the book.
—Journal of the American Statistical Association
Students found the presentation of the material and examples to be very helpful … an excellent book … I highly recommend this book for practising statisticians engaged in analysing univariate survival data. … This book will not only serve the statistical practitioner in the medical and pharmaceutical research areas well, but will be a convenient text for the lecturer aiming to include a useful applied component into a post-graduate statistics or operational research degree course.
—Journal of the Royal Statistical Society
The book would be a popular text for courses and a well-thumbed addition to any medical statistician’s collection. It is sufficiently general to be of interest to industrial statisticians concerned with lifetime testing but the focus is clearly on survival of patients under treatment.
—The Statistician
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Most Helpful Customer Reviews
2 of 2 people found the following review helpful:
5.0 out of 5 stars
Best non-technical introduction to survival analysis,
Amazon Verified Purchase(What's this?)
This review is from: Modelling Survival Data in Medical Research, Second Edition (Paperback)
I highly recommend this book to those interested in applications of lifetime data. It is probably the best non-technical introduction to survival analysis available. The book provides a good survey of topics and model diagnostics for survival analysis with just enough technical detail. This book is especially useful for model diagnostics. I know of no other book that approaches the quality of this book with respect to model diagnostics for survival models.
4 of 6 people found the following review helpful:
4.0 out of 5 stars
Good introduction,
By A Customer
This review is from: Modelling Survival Data in Medical Research (Chapman & Hall/CRC Texts in Statistical Science) (Hardcover)
A well-written introductory book. Broad range of material make it a good reference for new comers in survival analysis.
4.0 out of 5 stars
The cover is ok, with some small crease.,
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Amazon Verified Purchase(What's this?)
This review is from: Modelling Survival Data in Medical Research, Second Edition (Paperback)
The book is good, only I cannot understand survival analysis totally...Or it is because the teacher made it so theoretial that I cannot understand.
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Survival analysis is the phrase used to describe the analysis of data in the form of times from a well-defined time origin until the occurrence of some particular event or end-point. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
nephrectomy status, baseline cumulative hazard function, estimated pth percentile, accelerated failure time property, estimated survivor function, discontinuation time, estimated baseline survivor function, fitted survivor functions, procedure proc lifereg, accelerated failure time model, stained tumours, serum haemoglobin level, jth age group, estimated median survival time, martingale residuals, exponential survival times, fitted hazard function, procedure proc phreg, unit exponential distribution, analysing survival data, stained group, estimated cumulative hazard function, calculating the required number, jth explanatory variable, proportional hazards property New!
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- An Introduction to Generalized Linear Models, Second Edition by Annette J. Dobson in Front Matter, and Back Matter
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- Practical Statistics for Medical Research (Chapman & Hall/CRC Texts in Statistical Science) by Douglas G. Altman in Front Matter, and Back Matter
- Analysis of Failure and Survival Data by Peter J. Smith in Front Matter, and Back Matter
- Statistical Analysis of Reliability Data (Chapman & Hall/CRC Texts in Statistical Science) by Martin J. Crowder in Front Matter, and Back Matter
See all 75 books this book cites
- Medical Statistics from A to Z: A Guide for Clinicians and Medical Students by B. S. Everitt on 8 pages
- Primer of Biostatistics by Stanton A. Glantz on page 389, page 398, and page 408
- Analysis of Failure and Survival Data by Peter J. Smith in Front Matter, page 90, and Back Matter
- Data Analysis and Graphics Using R: An Example-based Approach (Cambridge Series in Statistical and Probabilistic Mathematics) by John Maindonald on page 283, and Back Matter
- Survival Analysis Using S: Analysis of Time-to-Event Data (Chapman & Hall/CRC Texts in Statistical Science) by Mara Tableman in Front Matter, and Back Matter
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