The Application of Psychometrics for Assessing Health Outcomes and Quality of Life (Part 2)
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ºù«Ӱҵ the course
The aim of this course is to provide participants with an introduction to advanced psychometric models in analysis of multi-item patient-reported outcome measures (PROMs).
The course will cover confirmatory factor analytic methods for categorical data, Rasch models, and other items response theory (IRT) models.
Feedback from previous attendees
"Really liked the mixture of exercises and taught material and how the tutors were open to supporting us along the way."
"Excellent presentations, delivered very clearly."
"Great advanced course content."
Who will benefit from the course?
The course content is aimed at participants with basic knowledge of psychometrics who want to apply advanced methods in scale construction and evaluation.
The course content is set at an intermediate/advanced level. It will focus on modern psychometric methods: factor analysis for categorical data, Rasch models, and other IRT models. 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:
- perform item-level confirmatory factor analysis (CFA) of PROMs using Mplus software
- understand the assumptions of CFA models, evaluate model fit, and revise the model
- understand the similarities and differences between CFA models, Rasch models and other IRT models
- perform IRT analyses using the Mplus software
- understand the assumptions of Rasch and IRT models and the principles for testing the models
- use results from IRT analyses to develop or select the optimal PROM for a particular research purpose
- be aware of the use of other software for CFA, Rasch and IRT analyses.
Course faculty
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 Individual modules are occasionally updated or withdrawn.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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