One-Day Introductory Training Workshop on Survival Analysis
Thursday 8 June 2017, 9.15am-5.00pm
This is a one-day workshop led by SLS Staff (Prof. Gillian Raab) on survival analysis for time to event data. The course is suitable for those with experience of statistical analyses but new to this type of analysis. It would be of particular interest to those considering using the Scottish Longitudinal Study to analyse time to event data.
This workshop will introduce methods to display and model time to event data, including Kaplan-Meier plots and Cox proportional hazards regression. The survival analysis theory will be complimented with hands-on practical sessions using either SPSS or Stata (R if sufficient interest is indicated) on training datasets similar to SLS data. Presentations of real projects will demonstrate research potential.
The course is intended for postgraduate students, academics and health or social researchers interested in learning how to do survival analysis in a statistical package. The course assumes some skills in statistical analysis, in particular a good knowledge of multiple regression and logistic regression would be beneficial. Additionally, a familiarity with using either SPSS, Stata or R syntax/command filesis essential.
The Scottish Longitudinal Study (SLS) links together administrative data for a 5.3% representative sample of the Scottish population (about 270,000 people). It includes information from the censuses (1991, 2001 and 2011), births, deaths, marriages, weather and pollution data, prescription data and education data from 2007 onwards. The SLS (with appropriate permissions) can also be linked to other health data sources such as cancer registry and hospital admission data from the NHS in Scotland. Analysis of the SLS data often involves time to an event of interest (e.g. death, hospital admission etc) and this requires survival analysis techniques.
- Features of survival data including censoring and truncation
- Plotting survival data
- Log-rank tests
- Hazard rates
- Cox proportional hazard model
Price: Standard Registration – £30; Fee Exemption – PhD students and Edinburgh University/ADRC staff/LONGPOP Early Stage Researchers
Lunch provided for all registered participants.
Places limited to 20 – Early registration is recommended.
For further info please contact email@example.com
This course is being jointly run by the LSCS and the European H2020 project “Methodologies and Data mining techniques for the analysis of Big Data based on Longitudinal Population and Epidemiological Registers” (LONGPOP)
August 7 - August 9, 2017 at Room 0G/010, Main Site Tower, Queen’s University Belfast, BT7 1NN