Data collected on the time to an event-such as the death of a patient in a medical study-is known as survival data. The methods for analyzing survival data can also be used to analyze data on the time to events such as the recurrence of a disease or relief from symptoms. Modelling Survival Data in Medical Research begins with an introduction to survival analysis and a description of four studies in which survival data was obtained. These and other data sets are then used to illustrate the techniques presented in the following chapters, including the Cox and Weibull proportional hazards models; accelerated failure time models; models with time-dependent variables; interval-censored survival data; model checking; and use of statistical packages. Designed for statisticians in the pharmaceutical industry and medical research institutes, and for numerate scientists and clinicians analyzing their own data sets, this book also meets the need for an intermediate text which emphasizes the application of the methodology to survival data arising from medical studies.
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
