DescriptionIn survival analysis, interest centres on "individuals" for each of whom there is a defined a point event called "failure", occurring after a length of time called the "failure time".Examples include lifetimes of machine components in industrial reliability, durations of strikes or periods of unemployment in economics, task completion times in psychological experiments and remission or survival times of patients in a clinical trial. Often, we may may wish to compare the failure times in two or more groups of individuals. Alternatively, values may be available for each individual of explanatory variables, thought to be related to survival; for example, white blood cell count is known to influence prognosis in leukaemia. The statistician's task is analyse the joint effect of several explanatory variables on survival. After developing an understanding of the basic concepts and statistical models, students may specialise into interesting areas of theory or application of survival analysis or into analysis of data using appropriate software such as R. Prerequisites Statistical Concepts II It is strongly recommended that students doing this project should also take Statistical Methods III. Topics in Statistics III may also be helpful. ResourcesWikipedia entry for Survival Analysis and links from it. Entry for Survival Analysis and related entries, in the Encylopedia of Statistical Sciences which may be found in the main library reference section (location Ref 519.503 ENC) Collett, Modelling Survival Data in Medical Research (2nd ed), Chapman and Hall/CRC 2003 (ISBN 1-58488-325-1) Crowder et al, Statistical Analysis of Reliability Data, Chapman and Hall 1991 (ISBN 0-412-59480-3)
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email: Peter Craig