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07-04-2022

A comparison of methods to address item non-response when testing for differential item functioning in multidimensional patient-reported outcome measures

Auteurs: Olawale F. Ayilara, Tolulope T. Sajobi, Ruth Barclay, Eric Bohm, Mohammad Jafari Jozani, Lisa M. Lix

Gepubliceerd in: Quality of Life Research | Uitgave 9/2022

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Abstract

Purpose

Item non-response (i.e., missing data) may mask the detection of differential item functioning (DIF) in patient-reported outcome measures or result in biased DIF estimates. Non-response can be challenging to address in ordinal data. We investigated an unsupervised machine-learning method for ordinal item-level imputation and compared it with commonly-used item non-response methods when testing for DIF.

Methods

Computer simulation and real-world data were used to assess several item non-response methods using the item response theory likelihood ratio test for DIF. The methods included: (a) list-wise deletion (LD), (b) half-mean imputation (HMI), (c) full information maximum likelihood (FIML), and (d) non-negative matrix factorization (NNMF), which adopts a machine-learning approach to impute missing values. Control of Type I error rates were evaluated using a liberal robustness criterion for α = 0.05 (i.e., 0.025–0.075). Statistical power was assessed with and without adoption of an item non-response method; differences > 10% were considered substantial.

Results

Type I error rates for detecting DIF using LD, FIML and NNMF methods were controlled within the bounds of the robustness criterion for > 95% of simulation conditions, although the NNMF occasionally resulted in inflated rates. The HMI method always resulted in inflated error rates with 50% missing data. Differences in power to detect moderate DIF effects for LD, FIML and NNMF methods were substantial with 50% missing data and otherwise insubstantial.

Conclusion

The NNMF method demonstrated comparable performance to commonly-used non-response methods. This computationally-efficient method represents a promising approach to address item-level non-response when testing for DIF.
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Metagegevens
Titel
A comparison of methods to address item non-response when testing for differential item functioning in multidimensional patient-reported outcome measures
Auteurs
Olawale F. Ayilara
Tolulope T. Sajobi
Ruth Barclay
Eric Bohm
Mohammad Jafari Jozani
Lisa M. Lix
Publicatiedatum
07-04-2022
Uitgeverij
Springer International Publishing
Gepubliceerd in
Quality of Life Research / Uitgave 9/2022
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI
https://doi.org/10.1007/s11136-022-03129-8

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