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  • Modelling Time-to-Event Data: Kaplan-Meier Survival Analysis and Cox Regression

    Author(s)
    Williams, Gail M.
    Ware, Robert S.
    Griffith University Author(s)
    Ware, Robert
    Year published
    2013
    Metadata
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    Abstract
    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
    DOI
    https://doi.org/10.1007/978-3-642-37131-8_11
    Subject
    Bioinformatics
    Publication URI
    http://hdl.handle.net/10072/336783
    Collection
    • Book chapters

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