Item response theory and structural equation modelling for ordinal data: Describing the relationship between KIDSCREEN and Life-H. (October 2016)

• Record Type: Journal Article
• Authors: Titman, Andrew C; Lancaster, Gillian A; Colver, Allan F
• Is Part Of: Statistical methods in medical research. Volume 25:Number 5(2016:Oct.)
• Page Start: 1892
• Page End: 1924
• Publication Date: 2016-10
• Subjects: item response theory -- structural equation modelling -- ordinal data -- health assessment -- cerebral palsy; Medicine -- Research -- Statistical methods -- Periodicals; Research -- Periodicals; Review Literature -- Periodicals; Statistics -- methods -- Periodicals; Médecine -- Recherche -- Méthodes statistiques -- Périodiques; 610.727
• DOI: 10.1177/0962280213504177
• Languages: English
• ISSNs: 0962-2802

Abstract

Both item response theory and structural equation models are useful in the analysis of ordered categorical responses from health assessment questionnaires. We highlight the advantages and disadvantages of the item response theory and structural equation modelling approaches to modelling ordinal data, from within a community health setting. Using data from the SPARCLE project focussing on children with cerebral palsy, this paper investigates the relationship between two ordinal rating scales, the KIDSCREEN, which measures quality-of-life, and Life-H, which measures participation. Practical issues relating to fitting models, such as non-positive definite observed or fitted correlation matrices, and approaches to assessing model fit are discussed. item response theory models allow properties such as the conditional independence of particular domains of a measurement instrument to be assessed. When, as with the SPARCLE data, the latent traits are multidimensional, structural equation models generally provide a much more convenient modelling framework.