Introduction to data linkage

This short course is designed to give participants a practical introduction to data linkage. It 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 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.

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Agenda

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: Tuesday 22 October, 9:30 - 16:45 and Wednesday 23 October, 9:30 - 16:45

Format: In-person

Location: London 

Cost: 

• £35 per day for students registered at any University
• £75 per day for staff at academic institutions, Research Councils researchers, public sector staff and staff at registered charity organisations and recognised research institutions
• £250 per day for all other participants.

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