Evaluating linkage quality for the analysis of linked data – Oxford


Computer software and computer workshops This event includes computer workshops. Participants will need to bring their own laptops with a Windows operating system with Excel, and LinkPlus software (freely available from the Centers for Disease Control and Prevention website) Please note LinkPlus is not compatible with Macs.

This is a training and capacity building event co-organised by the Administrative Data Research Centre England (ADRCE) and the Consumer Data Research Centre (CDRC).

This short course is designed to give participants a practical introduction to handling and evaluating the 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.

We recommend this course is booked in conjunction with Introduction to data linkage and analysing linked data on the 10th May 2018, but it can also be booked as a separate one day course. This separate course will cover examples of the uses of data linkage, data preparation, and methods for linkage (including deterministic and probabilistic approaches and privacy-preserving linkage).

Target audience:

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.

Experience of using Stata or other software will be useful for the practical session.

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 question

Learning outcomes:

- Evaluate the success of data linkage

- Understand the implications of linkage error on analysis of linked data

- Appropriately report analysis based on linked data

Course outline:

- Data processing

- Merging and restructuring data

- Linkage error and bias

- Classifying linkage designs

- Evaluating the impact of linkage error in analysis

- Reporting of linkage studies