Evaluating Linkage Quality for the Analysis of Linked Data
Date:
23/03/2018
Organised by:
ADRC-E/University of Southampton
Presenter:
Dr Katie Harron and Dr James Doidge
Level:
Entry (no or almost no prior knowledge)
Contact:
Description:
Course places are limited and registration by 15 March 2018 is strongly recommended
Course No. ADRCE-Training057 Harron
This course is organised by ADRC-E/University of Southampton
We recommend this course is booked in conjunction with ADRC-E Short Course T052 Introduction to Data Linkage on the 22nd March 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 22nd of March 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).
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 and please note that participants will need to bring their own laptops with their data management or statistical software of choice
Presenter
Katie Harron is a Senior Lecturer in Quantitative Methods at UCL GOS Institute of Child Health and the Administrative Data Research Centre for England. Katie is a statistician with research interests in using linkage of administrative data and electronic health records for health research. Her current research involves establishing how nationally representative, population-level administrative data can be used to identify and measure determinants of variation in service use and educational outcomes for children born preterm by linking information on maternal, household and social environments. Katie completed her PhD in Statistics at University College London. She is a co-editor of a Wiley commissioned book “Methodological developments in data linkage” with Prof Harvey Goldstein and Prof Chris Dibben.
James Doidge is a Senior Research Associate at UCL GOS Institute of Child Health and the Administrative Data Research Centre for England. James’s interests in research methods and evidence-based public policy have led to experience in a wide range of research fields, including child health and development, child protection and the social determinants of health, nutrition, education and crime. His current role focuses on driving forward the utilisation of large linked administrative datasets for research purposes, through development of relevant statistical methods and exemplary studies that demonstrate the potential value of these data.
Target Audience
The course is aimed at researchers who need to gain an understanding of how the data linkage process might impact on the analysis of linked data. The course provides an introduction to classifying data linkage designs and evaluating linkage error, in order to understand potential implications for analysis. Participants may be academic researchers in the social and health sciences or may work in government, survey agencies, and official statistics, for charities or the private sector.
The course will start with registration and coffee at 9.30am with formal teaching starting at 9:45am and finishing at 4.30pm. Afterwards there will be an opportunity for participants to ask questions about the course and to discuss with the instructor how to link their own datasets (you can bring your own data to the course if you wish).
Pre-requisites
The course does not assume any prior knowledge of data linkage. Some experience of using Excel will be useful for the practical session.
You can find additional information on Data Linkage by Dr Harron at the following links:
- ADRC-E podcast > https://adrn.ac.uk/about/network/england/training-podcasts/
- ADRN guide > https://adrn.ac.uk/media/174220/data_linkage_final.pdf
Cost:
1. £30 - For UK registered postgraduate students
2. £60 – For staff at UK academic institutions, Research Council UK funded researchers, UK public sector staff and staff at UK registered charity organisations
3. £220 - For all other participants
4. Free Place for ADRC/ADRN/ADS staff
All fees include event materials, lunch, morning and afternoon tea. They do not include travel and accommodation costs.
Website and registration:
Region:
Greater London
Keywords:
Longitudinal Research , Quality in Quantitative Research, Data linkage, Use of Administrative Sources
Related publications and presentations:
Longitudinal Research
Quality in Quantitative Research
Data linkage