Evaluating Linkage Quality for the Analysis of Linked Data
We are pleased to offer you this short course jointly organised by the Administrative Data Research Centre for England (ADRC-E) and the Consumer Data Research Centre (CDRC).
We recommend this course is booked in conjunction with ADRCE Short Course T055 Introduction to Data Linkage on the 10 May 2018, but it can also be booked as a single day course.
This short course is designed to give participants a practical introduction to handling and evaluating quality of linked data, and is aimed at researchers who want to understand more about how the data linkage process might impact on results derived from linked data. We will cover processing of linked data, concepts of linkage error and bias, and evaluating how linkage error might impact on analysis. This course includes a mixture of lectures and group work that will enable participants to put theory into practice.
Introduction to Data Linkage is a separate course on the 10 May which will cover examples of the uses of data linkage, data preparation, and methods for linkage (including deterministic and probabilistic approaches and privacy-preserving linkage).
Further course details can be found here.
More information regarding our courses can be found here.
Podcast for some of our previous courses can be found here.
Course Tutors: Dr Katie Harron, Dr James Doidge
The course covers:
- Data processing
- Classifying linkage designs
- Evaluating linkage quality and bias
- Reporting analysis of linked data
- Understanding the implications of linkage error using example research questions
Learning Outcomes:
By the end of the course participants will:
- Evaluate the success of data linkage
- Understand the implications of linkage error on analysis of linked data
- Appropriately report analysis based on linked data
Computer Software and Computer workshops
This event includes computer workshops. Please note that participants will need to bring their own laptops with their data management or statistical software of choice