Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Item response theory and Structural Equation Modelling for ordinal data
T2 - describing the relationship between KIDSCREEN and Life-H
AU - Titman, Andrew
AU - Lancaster, Gillian
AU - Colver, Allan
PY - 2016/10
Y1 - 2016/10
N2 - 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.
AB - 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.
KW - item response theory
KW - structural equation modelling
KW - ordinal data
KW - health assessment
KW - cerebral palsy
U2 - 10.1177/0962280213504177
DO - 10.1177/0962280213504177
M3 - Journal article
VL - 25
SP - 1892
EP - 1924
JO - Statistical Methods in Medical Research
JF - Statistical Methods in Medical Research
SN - 0962-2802
IS - 5
ER -