One-Day Introductory Training Workshop for the Scottish Longitudinal Study (SLS)

Wednesday 7 June 2017, 9.30am-4.30pm

The Scottish Longitudinal Study (SLS) links together routinely collected administrative data for a 5.3% representative sample of the Scottish population (about 270,000 people). It includes a wealth of information from the censuses (1991 to 2011), vital events registrations (births, deaths, marriages), weather and pollution 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.

The size and scope of the SLS make it an unparalleled resource for analysing a range of socio-economic, demographic and health questions, including those which are based on reasonably rare events. The longitudinal nature of the SLS is particularly valuable, it provides insights into the health and social status of the Scottish population and, how it changes over time.

The course content will include:

  • Introducing the SLS and the main data sources that are linked, including Census data, Vital Events data (births, deaths, marriages) and Education data
  • Examples of the types of studies that could be undertaken using the SLS
  • Detailed information about how to access the SLS
  • An overview of the possibilities to link the SLS to NHS health data (cancer registry and hospital admission data, etc)
  • An introduction to the online Data Dictionary and a hands-on computer lab in SPSS
  • The new SLS Birth Cohort of 1936 (SLSBC1936) and SLS future developments

Standard Registration: £15 to cover lunch and printing.  Fee Exemption: University of Edinburgh PhD students/UoE and ADRC staff/LONGPOP EARLY STAGE RESEARCHERS

Booking 

For further details please contact: angela.fallon@ed.ac.uk

Places on the course are limited  so early booking is recommended.

 

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)

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