Modelling Time-to-Event Data: Kaplan-Meier Survival Analysis and Cox Regression
Author(s)
Williams, Gail M.
Ware, Robert S.
Griffith University Author(s)
Year published
2013
Metadata
Show full item recordAbstract
Much clinical research involves following up patients to an adverse outcome, which could be death, relapse, an adverse drug reaction or the development of a new disease. In these studies, time to event needs to be modelled such that factors that delay such events can be determined. The set of statistical procedures used to analyze such data is collectively termed survival analysis and is a very useful tool in clinical research. This chapter introduces the different tools of survival analysis.Much clinical research involves following up patients to an adverse outcome, which could be death, relapse, an adverse drug reaction or the development of a new disease. In these studies, time to event needs to be modelled such that factors that delay such events can be determined. The set of statistical procedures used to analyze such data is collectively termed survival analysis and is a very useful tool in clinical research. This chapter introduces the different tools of survival analysis.
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Book Title
Methods of Clinical Epidemiology
Subject
Bioinformatics