Survival Analysis

Date:

06/10/2020 - 07/10/2020

Organised by:

Royal Statistical Society

Presenter:

Dr Dave Collett

Level:

Advanced (specialised prior knowledge)

Contact:

training@rss.org.uk

Map:

View in Google Maps  (EC1Y 8LX)

Venue:

12 Errol Street, London

Description:

Course Outline

Standard methods of survival analysis based on the Kaplan-Meier estimate of a survivor function, the log rank test and Cox regression modelling are widely used in many different areas of application.   But often, the assumptions that underlie these techniques may not be valid, or the data structure may be more complex.  Extensions of these basic methods allow particular features of data that occur in practice to be handled appropriately.  This course will begin with an overview of standard methods and then move on to some of the more advanced techniques.  Their practical application will be illustrated using SAS and R.

Learning Outcomes

An appreciation of how the methods of survival analysis can be used in a variety of situations.

Topics Covered

Overview of standard methods for summarising survival data and the Cox regression model.  Model selection strategy.  Incorporating time dependent variables and the counting process formulation of survival data.  Parametric models for survival data, including flexible models based on splines.  Detecting and handling non proportional hazards.  Incorporating random effects into a survival analysis; frailty models.  Analysis of data where there is more than one type of event; models for competing risks. Dependent censoring.

Target Audience

Statisticians and epidemiologists in public sector research organisations, pharmaceutical companies and related organisations.  University research students and fellows.

Cost:

Ranges from £588-£816 inc. VAT

Website and registration:

Region:

Greater London

Keywords:

Statistical Theory and Methods of Inference, Cox

Related publications and presentations:

Statistical Theory and Methods of Inference

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