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18-06-2022

Accuracy of mixture item response theory models for identifying sample heterogeneity in patient-reported outcomes: a simulation study

Auteurs: Tolulope T. Sajobi, Lisa M. Lix, Lara Russell, David Schulz, Juxin Liu, Bruno D. Zumbo, Richard Sawatzky

Gepubliceerd in: Quality of Life Research | Uitgave 12/2022

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Abstract

Purpose

Mixture item response theory (MixIRT) models can be used to uncover heterogeneity in responses to items that comprise patient-reported outcome measures (PROMs). This is accomplished by identifying relatively homogenous latent subgroups in heterogeneous populations. Misspecification of the number of latent subgroups may affect model accuracy. This study evaluated the impact of specifying too many latent subgroups on the accuracy of MixIRT models.

Methods

Monte Carlo methods were used to assess MixIRT accuracy. Simulation conditions included number of items and latent classes, class size ratio, sample size, number of non-invariant items, and magnitude of between-class difference in item parameters. Bias and mean square error in item parameters and accuracy of latent class recovery were assessed.

Results

When the number of latent classes was correctly specified, the average bias and MSE in model parameters decreased as the number of items and latent classes increased, but specification of too many latent classes resulted in modest decrease (i.e., < 10%) in the accuracy of latent class recovery.

Conclusion

The accuracy of MixIRT model is largely influenced by the overspecification of the number of latent classes. Appropriate choice of goodness-of-fit measures, study design considerations, and a priori contextual understanding of the degree of sample heterogeneity can guide model selection.
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Metagegevens
Titel
Accuracy of mixture item response theory models for identifying sample heterogeneity in patient-reported outcomes: a simulation study
Auteurs
Tolulope T. Sajobi
Lisa M. Lix
Lara Russell
David Schulz
Juxin Liu
Bruno D. Zumbo
Richard Sawatzky
Publicatiedatum
18-06-2022
Uitgeverij
Springer International Publishing
Gepubliceerd in
Quality of Life Research / Uitgave 12/2022
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI
https://doi.org/10.1007/s11136-022-03169-0

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