Introductory Analysis of Linked Health Data

The Introductory Analysis of Linked Health Data is an intensive five-day course on the theory and practice of analysis of large sets of linked health and social data at an introductory to intermediate level.

Applications are now open for the course 12 February - 16 February 2018.

Rapid growth in data linkage projects has led to a shortfall in analyst skills. Some researchers understand epidemiological principles, but are unfamiliar with the specialised computing skills needed to analyse linked data files.

Others have a strong grasp of computing concepts, but lack an adequate theoretical base to design high quality applications to answer research questions. This course endeavours to fill a gap in training opportunities to cater to these two areas of need.

Course Outline

The course caters to users of SPSS, SAS, Stata or R with course materials and exercises covering all three statistical software packages.  The course provides a theoretical grounding in the classroom on each topic, followed by a practical training session on the corresponding computing solutions.

Students use fictitious but realistic linked data files in the hands-on exercises.  The course instructor is available in the computing laboratory session each afternoon and conducts one-on-one coaching for those who need assistance.

Who Should Attend

This course is ideal for health and social care researchers, social scientists, clinical practitioners and health care managers who wish to build on their pre-existing theoretical knowledge and skills in the analysis of linked health data.

Learning Objectives

The course acquaints health and social researchers, clinical practitioners and managers with the theory and skills needed to analyse linked health and social data at the introductory to intermediate level.

Upon completion the participant will:

  • possess an overview of the theory of data linkage methods and features of comprehensive data linkage systems, sufficient to understand the sources and limitations of linked data sets;

  • understand the principles of epidemiologic measurement and research methods for the conceptualisation and construction of numerators and denominators used in the analysis of health and social phenomena, including services utilisation and outcomes;

  • understand sources of measurement error in linked data, the difference between confounding and effect modification, and use of regression models in risk adjustment in health and social research;

  • be able to perform statistical analyses on linked longitudinal health and social data;

  • be able to conceptualise and perform the manipulation of large linked data files; and

  • be able to write statistical syntax to prepare linked data files for analysis, derive exposure and outcome variables, relate numerators and denominators and produce results from statistical procedures.

Course Prerequisites

Basic familiarity with computing syntax used in either SPSS, SAS, Stata or R and methods of basic statistical analysis of fixed-format data files.

There are no formal prerequisites in epidemiology for the course.  However, it is recommend that participants who have not previously completed an introductory course in epidemiology, familiarise themselves with the basic principles and terms used in that discipline.  A working knowledge of statistical concepts, including regression models, used in data analysis in the medical and social sciences is assumed.

Course Credits

The Introductory Analysis of Linked Health Data Course is part of the MSc Health Data Science module (PMIM302) which carries 20 Masters Level Credits and these are awarded on completion of a successful assignment. 

However, students who wish to attend for Continuing Professional Development (CPD) purposes only, will omit the assessment and be given a Certificate of Attendance.

Course Fees

Commercial: £1560.00 per delegate

Non-commercial: £1260.00 per delegate

Full-time PhD student unwaged: £695.00 per delegate

(International students please enquire for further details of course fees)

Fees include course materials.


To apply, please complete the form here.

Please note that registration forms received after the closing date will incur a £50 late booking fee.

The training courses are delivered in collaboration with

     The Centre for Health Services Research at

UWA Logo - March 17

Contact Us

Course Enquiries:
Tony Paget
Associate Professor & Course Director
MSc Health Informatics, MSc Health Data Science and MRes Health Informatics

Marketing Enquiries:
Stephanie Lee

Data Science Building, Swansea University Medical School, Singleton Park, SWANSEA SA2 8PP, Wales, UK

+44 (0)1792 602874