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Gepubliceerd in: Quality of Life Research 3/2015

01-03-2015 | Response Shift and Missing Data

RespOnse Shift ALgorithm in Item response theory (ROSALI) for response shift detection with missing data in longitudinal patient-reported outcome studies

Auteurs: Alice Guilleux, Myriam Blanchin, Antoine Vanier, Francis Guillemin, Bruno Falissard, Carolyn E. Schwartz, Jean-Benoit Hardouin, Véronique Sébille

Gepubliceerd in: Quality of Life Research | Uitgave 3/2015

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Abstract

Purpose

Some IRT models have the advantage of being robust to missing data and thus can be used with complete data as well as different patterns of missing data (informative or not). The purpose of this paper was to develop an algorithm for response shift (RS) detection using IRT models allowing for non-uniform and uniform recalibration, reprioritization RS recognition and true change estimation with these forms of RS taken into consideration if appropriate.

Methods

The algorithm is described, and its implementation is shown and compared to Oort’s structural equation modeling (SEM) procedure using data from a clinical study assessing health-related quality of life in 669 hospitalized patients with chronic conditions.

Results

The results were quite different for the two methods. Both showed that some items of the SF-36 General Health subscale were affected by response shift, but those items usually differed between IRT and SEM. The IRT algorithm found evidence of small recalibration and reprioritization effects, whereas SEM mostly found evidence of small recalibration effects.

Conclusion

An algorithm has been developed for response shift analyses using IRT models and allows the investigation of non-uniform and uniform recalibration as well as reprioritization. Differences in RS detection between IRT and SEM may be due to differences between the two methods in handling missing data. However, one cannot conclude on the differences between IRT and SEM based on a single application on a dataset since the underlying truth is unknown. A next step would be to implement a simulation study to investigate those differences.
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Metagegevens
Titel
RespOnse Shift ALgorithm in Item response theory (ROSALI) for response shift detection with missing data in longitudinal patient-reported outcome studies
Auteurs
Alice Guilleux
Myriam Blanchin
Antoine Vanier
Francis Guillemin
Bruno Falissard
Carolyn E. Schwartz
Jean-Benoit Hardouin
Véronique Sébille
Publicatiedatum
01-03-2015
Uitgeverij
Springer International Publishing
Gepubliceerd in
Quality of Life Research / Uitgave 3/2015
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI
https://doi.org/10.1007/s11136-014-0876-4

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