Advanced Survival Analysis
An online short course
This course aims to explain and implement parametric survival models, to use flexible parametric survival models and to introduce the concept of competing risks in modelling time-to-event data.
|Course date||5 July 2021|
|Course Organisers||Dr Sue Ingle|
Please ensure you meet the following prerequisites before booking:
|Knowledge||Participants should be familiar with using Stata statistical software and implementing survival analyses within Stata. Participants should also be familiar with the basics of survival analysis, to at least the level attained from the short course on Introduction to Rates and Survival Analysis.|
|Software||You must have Stata (version 11 or later, though we recommend more recent versions)* installed in advance of the course.
*Internal University of Bristol participants will be provided with access to Stata version 16 on the first day of the course.
This 1-day course will run online using Blackboard Collaborate.
By the end of the course students should be able to:
- analyse data using Poisson, Cox and parametric (e.g. Weibull) regression models;
- describe the links between these approaches;
- use flexible parametric survival analysis to improve model fit to the data;
- analyse survival data with competing outcomes
Who the course is intended for
This course is intended for medical statisticians. Applicants should be competent users of Stata and should be familiar with basic survival analysis eg Cox models, equivalent to the level taught in Introduction to Rates and Survival Analysis short course.
- Parametric survival models
- Fexible parametric survival models
- Competing risks in survival analysis
Online Course Bookings
Bookings are open for online courses running in 2021.
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Find out more
We may need to make responsive changes to our courses at short notice in order to follow the latest Public Health, Government and University guidance on coronavirus (COVID-19).