17/07/2024 - 18/07/2024

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 material that will enable participants to put theory into practice.  

The course is led by Professor Katie Harron from UCL - project lead for the ADR England-funded Education and Child Health Insights from Linked Data (ECHILD) project - and Dr James Doidge from the Intensive Care National Audit and Research Centre.

Find out more and register


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.

Event details

Date: Wednesday 17 July, 9:30 - 17:00 and Thursday 18 July, 9:30 - 17:00

Format: Online 

Cost: £150 for students, £401 for other participants

Registration: Visit the full information page for details on how to register.

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