Training and Events
Introduction to Data Linkage
|ADRC-E/University of Southampton|
Dr Katie Harron
The Farr Institute, 222 Euston Rd, Kings Cross, London
View in Google Maps (NW1 2DA)
Course places are limited and registration by 15 March 2018 is strongly recommended
Course No. ADRCE-Training052 Harron
We are pleased to offer you this short course organised by the Administrative Data Research Centre for England (ADRC-E)
Short Summary of Course
We recommend this course is booked in conjunction with ADRC-E Short Course T057 Evaluating linkage quality for the analysis of linked data on the 23rd March 2018, but it can also be booked as a separate one day course.
This short course is designed to give participants a practical introduction to data linkage and is aimed at researchers either intending to use data linkage themselves or those who want to understand more about the process so that they can analyse linked data. Introduction to Data Linkage 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 main focus of this course will be health data, although the concepts will apply to many other areas. This course includes a mixture of lectures and practical sessions that will enable participants to put theory into practice.
Evaluating linkage quality for the analysis of linked data is a separate course on the 23rd March, which will cover processing of linked data, concepts of linkage error and bias, and handling linkage error in analysis.
The course covers:
By the end of the course participants will:
Computer Software and Computer workshops
This event includes computer workshops.
Participants will need to bring their own laptops with Excel (or other data management software) and Link Plus software. Link Plus is freely available from http://www.cdc.gov/cancer/npcr/tools/registryplus/lp_tech_info.htm. Please note that this software requires a Windows operating system (Macs will not work).”
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.
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..
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).
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:
Entry (no or almost no prior knowledge)
1. £30 - For UK registered postgraduate students
Website and registration
Longitudinal Research , Quality in Quantitative Research, Data linkage, Use of Administrative Sources
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