Introduction to Data Linkage (few places remaining)

Date:

13/09/2023 - 14/09/2023

Organised by:

University College London

Presenter:

Professor Katie Harron and Dr James Doidge

Level:

Entry (no or almost no prior knowledge)

Contact:

Short Course Coordinator
ioe.shortcourses@ucl.ac.uk

Map:

View in Google Maps  (WC1E 7HU)

Venue:

University of London
Senate House
Malet Street
London

Description:

This short course is designed to give participants a practical introduction to data linkage and is aimed at both analysts intending to link data themselves and researchers who want to understand more about the linkage process and its implications for analysis of linked data—particularly the implications of linkage error. Day 1 will focus on the methods and practicalities of data linkage (including deterministic and probabilistic approaches) using worked examples. Day 2 will focus more on analysis of linked data, including concepts of linkage error, how to assess linkage quality and how to account for the resulting bias and uncertainty in analysis of linked data. Examples will be drawn predominantly from health data, but the concepts will apply to many other areas. This course includes a mixture of lectures and practical sessions that will enable participants to put theory into practice.  

The course covers:

  • Overview of data linkage (data linkage systems, benefits of data linkage, types of projects)
  • Overview of linkage methods (deterministic and probabilistic, privacy-preserving)
  • The linkage process (data preparation, blocking, classification)
  • Classifying linkage designs
  • Evaluating linkage quality and bias (types of error, analysis of linked data)
  • Reporting analysis of linked data
  • Practical sessions

By the end of the course participants will:

  • Understand the background and theory of data linkage methods
  • Design deterministic and probabilistic linkage strategies
  • Evaluate the success of data linkage
  • Appropriately report analysis based on linked data

The course is aimed at researchers who need to gain an understanding of data linkage techniques and of how to analyse linked data. The course provides an introduction to data linkage theory and methods for those who might be using linked data in their own work. Participants may be academic researchers in the social and health sciences or may work in government, survey agencies, official statistics, for charities or the private sector.  The course does not assume any prior knowledge of data linkage. Some experience of using Excel or other software will be useful for the practical sessions.

 

Cost:

The fee per teaching day is:• £35 per day for registered students• £75 per day for staff at academic institutions, Research Councils researchers, public sector staff, staff at registered charity organisations and recognised research institutions. • £250 per day for all other participants. In the event of cancellation by the delegate a full refund of the course fee is available up to two weeks prior to the course. No refunds are available after this date.If it is no longer possible to run a course due to circumstances beyond its control, NCRM reserves the right to cancel the course at its sole discretion at any time prior to the event. In this event every effort will be made to reschedule the course. If this is not possible or the new date is inconvenient a full refund of the course fee will be given. NCRM shall not be liable for any costs, losses or expenses that may be incurred as a result of the cancellation of a course. The University of Southampton’s Online Store T&Cs also continue to apply.

Website and registration:

Region:

Greater London

Keywords:

Data linkage

Related publications and presentations:

Data linkage

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