Event box

3 day course which runs from Monday midday to Thursday midday:  25th - 28th February 2019.

In many medical applications interest lies in times to or between events. Examples include time from diagnosis of cancer to death, or times between epileptic seizures. This course begins with a review of standard approaches to the analysis of censored survival data. Survival models and estimation procedures are reviewed, and emphasis is placed on the underlying assumptions, how these might be evaluated through diagnostic methods and how robust the primary conclusions might be to their violation. Issues relating to choice of end point, censoring and the appropriate use of time dependent covariates are discussed. The course also includes a description of models and methods for the treatment of multivariate survival data, such as competing risks data, recurrent events or the lifetimes of family members. Each lecture is complemented by a practical session implementing the methods using R.

Important please note:

We will make every attempt to accommodate Lancaster University staff and postgraduate research students on our courses. However, if a course becomes fully booked we reserve the right to give priority to students on the MSc in Statistics, MSc in Data Science, and external participants.

 

Details of course fees.

Payment: Once you have registered, please pay at the online shop 

https://online-payments.lancaster-university.co.uk/product-catalogue/courses/mathematics-and-statistics/short-courses-and-cpd/mps-research-unit-psc-short-courses-20182019

Accommodation Details: Can be found here.

Cancellation Policy

Registrations are transferable to another course or individual at any time. Full refunds will be given for cancellation 10 or more working days before the course start date. Otherwise the full course fee will be charged.


Date:
Monday, February 25, 2019
Time:
1:00pm - 1:00pm
Location:
Postgraduate Statistics Centre
Presenter:
Dr Andrew Titman
Type:
Taught Session - For Externals, Staff & Students

Programme:

Survival, hazard and cumulative hazard functions
Kaplan-Meier plots
Parametric models and likelihood construction
Cox proportional hazards model and partial likelihood
Time-dependent covariates
Diagnostic methods
Truncated and interval censored data
Testing the proportional hazards assumption
Competing risks, recurrent events and frailty models



Registration is now closed. See the events page for details of future sessions.

Non-attendance