Modelling Survival Data in Medical Research
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Book Description
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.
Book Info
Text describes and illustrates the modeling approach to the analysis of survival data. Includes revised and updated material, reflecting the developments and advancements made over the last ten years. Serves as a text for upper-level and graduate courses in survival analysis and biostatistics. Previous edition: c1994. Softcover.
--This text refers to an out of print or unavailable edition of this title.
Modelling Survival Data in Medical Research,David Collett,Chapman & Hall/CRC,0412448904,Biostatistics,Linear models (Statistics),Medical,Medical / Nursing,Medicine,Prognosis,Research,Science/Mathematics,Statistical methods
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