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Item response theory and Structural Equation Modelling for ordinal data: describing the relationship between KIDSCREEN and Life-H

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<mark>Journal publication date</mark>10/2016
<mark>Journal</mark>Statistical Methods in Medical Research
Issue number5
Number of pages33
Pages (from-to)1892-1924
Publication StatusPublished
Early online date9/10/13
<mark>Original language</mark>English


Both item response theory (IRT) and structural equation modelling (SEM) are useful in the analysis of ordered categorical responses from health assessment questionnaires. We highlight the advantages and disadvantages of the IRT and SEM approaches to modelling ordinal data, from within a community health setting. Using data from the SPARCLE project focussing on children with cerebal 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. IRT 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, SEMs generally provide a much more convenient modelling framework.