The Application of Psychometrics for Measuring Health Outcomes and Quality of Life (Part 1)
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About the course
The aim of this two-day course is to provide participants with an introduction to psychometrics as applied to health. It will cover the core psychometric and statistical methods used in scale construction and the development of multi-item patient-reported outcome measures (PROMs).
The course will be interactive and practical. Sessions will be delivered using lectures and individual and small group practical exercises using real-world examples.
Feedback from previous attendees
"The course delivery was excellent. The content was delivered clearly and in an accessible manner."
"Delivery speed and pace was good - as were the tasks alongside to consolidate knowledge learnt."
"Really great course."
Who will benefit from the course?
The course content is aimed at participants with no prior knowledge of psychometrics, or those who wish to refresh and gain more theoretical and practical knowledge in this area.
The course content is set at a basic/intermediate level. It will focus on classical methods of test construction and test of differential item function, but will also provide an introduction to modern psychometric methods such as Rasch models, item response theory and factor analysis for categorical data. It will be relevant to researchers, students, clinicians and other health care professionals and members of the pharmaceutical industry interested in using or developing PROMs.
Learning outcomes
By the end of this course participants should be able to:
- identify the key stages involved in scale construction and development
- understand the qualitative process involved in the development of a PROM and item generation
- describe the different ways of scoring and scaling a PROM and the theory underpinning these
- understand exploratory (EFA) and confirmatory (CFA) factor analysis and be able to carry out EFA using SPSS
- understand what is meant by reliability, validity, and responsiveness and be able to analyse and interpret these using SPSS
- explore the above concepts using datasets from a range of existing disease-specific and generic PROMs
- be aware of the use of different software other than SPSS where applicable.
Further learning: Part 2 (Advanced)
An advanced course will immediately follow part 1. This will cover Rasch models, item response theory, confirmatory factor analysis and factor analysis for categorical data in more detail using MPlus software.
Course faculty
Professor Jill Carlton, Professor of Health Outcomes Research, School of Medicine and Population Health
Dr Tessa Peasgood, Senior Lecturer in Health Economics, School of Medicine and Population Health
Dr Philip Powell, Senior Research Fellow, School of Medicine and Population Health
The content of our courses is reviewed annually to make sure it is up-to-date and relevant. Individual modules are occasionally updated or withdrawn. This is in response to discoveries through our world-leading research, funding changes, professional accreditation requirements, student or employer feedback, outcomes of reviews, and variations in staff or student numbers. In the event of any change we'll consult and inform students in good time and take reasonable steps to minimise disruption.
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