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Gepubliceerd in:

21-01-2022 | Special Section: Non-parametric IRT

Non-parametric measurement for patient-reported outcomes

Auteur: Jan R. Boehnke

Gepubliceerd in: Quality of Life Research | Uitgave 1/2022

Excerpt

We issued the call for the set of papers published in this special section in 2019 with the goal to illuminate innovative state-of-the-art methods for nonparametric measurement. The original idea for this call goes back to a series of potential topics for methodological special sections in our journal collated by our previous Co-Editor in Chief, Frans J. Oort, which we discussed and developed further in our editorial meetings at the International Society for Quality of Life Research (ISOQOL) Annual Conferences in Philadelphia (2017) and Dublin (2018). And I am very grateful to our two excellent guest editors, Klaas Sijtsma and Andries van der Ark, who helped us to finalize the call and who facilitated the project. We received 13 expressions of interest and six full papers were submitted, of which five are published in this special section. …

vorige artikel Evaluation of the link between the Guttman errors and response shift at the individual level

volgende artikel Evidence on the relationship between PROMIS-29 and EQ-5D: a literature review

Guttman, L. (1947). The Cornell technique for scale and intensity analysis. Educational and Psychological Measurement, 7(2), 247–279. https://doi.org/10.1177/001316444700700204CrossRefPubMed

van der Linden, W. J., & Hambleton, R. K. (1997). Nonparametric models. Handbook of modern item response theory (pp. 347–349). Springer.CrossRef

Sijtsma, K., & Van der Ark, L. A. (2001). Progress in NIRT analysis of polytomous item scores: Dilemmas and practical solutions. In A. Boomsma, M. A. J. Van Duijn, & T. A. B. Snijders (Eds.), Essays on item response theory (pp. 297–318). Springer.CrossRef

Sijtsma, K., & van der Ark, L. A. (2017). A tutorial on how to do a Mokken scale analysis on your test and questionnaire data. British Journal of Mathematical and Statistical Psychology, 70(1), 137–158. https://doi.org/10.1111/bmsp.12078CrossRef

Junker, B. (2001). On the interplay between nonparametric and parametric IRT, with some thoughts about the future. In A. Boomsma, M. A. J. Van Duijn, & T. A. B. Snijders (Eds.), Essays on item response theory (pp. 247–276). Springer.CrossRef

Meijer, R. R., Tendeiro, J. N., & Wanders, R. B. K. (2015). The use of nonparametric item response theory to explore data quality. Handbook of item response theory modeling: Applications to typical performance assessment (pp. 85–110). Taylor & Francis (Routledge).

Sijtsma, K., & van der Ark, L. A. (2021). Advances in nonparametric item response theory for scale construction in quality-of-life research. Quality of Life Research. https://doi.org/10.1007/s11136-021-03022-wCrossRefPubMedPubMedCentral

Feng, Y. S., Jiang, R., Pickard, A. S., & Kohlmann, T. (2021). Combining EQ-5D-5L items into a level summary score: Demonstrating feasibility using non-parametric item response theory using an international dataset. Quality of Life Research. https://doi.org/10.1007/s11136-021-02922-1CrossRefPubMedPubMedCentral

Falk, C. F., & Fischer, F. (2021). More flexible response functions for the PROMIS physical functioning item bank by application of a monotonic polynomial approach. Quality of Life Research. https://doi.org/10.1007/s11136-021-02873-7CrossRefPubMedPubMedCentral

10.

Koopman, L., Zijlstra, B. J. H., & van der Ark, L. A. (2021). A two-step, test-guided Mokken scale analysis, for nonclustered and clustered data. Quality of Life Research. https://doi.org/10.1007/s11136-021-02840-2CrossRefPubMedPubMedCentral

11.

Crisan, D. R., Tendeiro, J. N., & Meijer, R. R. (2021). The Crit coefficient in Mokken scale analysis: A simulation study and an application in quality-of-life research. Quality of Life Research. https://doi.org/10.1007/s11136-021-02924-zCrossRefPubMedPubMedCentral

12.

Straat, J. H., van der Ark, L. A., & Sijtsma, K. (2014). Minimum sample size requirements for Mokken scale analysis. Educational and Psychological Measurement, 74(5), 809–822. https://doi.org/10.1177/0013164414529793CrossRef

13.

Dubuy, Y., Sebille, V., Grall-Bronnec, M., Challet-Bouju, G., Blanchin, M., & Hardouin, J. B. (2021). Evaluation of the link between the Guttman errors and response shift at the individual level. Quality of Life Research. https://doi.org/10.1007/s11136-021-03015-9CrossRefPubMed

14.

Blanchin, M., Sebille, V., Guilleux, A., & Hardouin, J. B. (2016). The Guttman errors as a tool for response shift detection at subgroup and item levels. Quality of Life Research, 25(6), 1385–1393. https://doi.org/10.1007/s11136-016-1268-8CrossRefPubMed

15.

Rapkin, B. D., & Schwartz, C. E. (2019). Advancing quality-of-life research by deepening our understanding of response shift: A unifying theory of appraisal. Quality of Life Research. https://doi.org/10.1007/s11136-019-02248-zCrossRefPubMedPubMedCentral

16.

Vanier, A., Oort, F. J., McClimans, L., Ow, N., Gulek, B. G., Bohnke, J. R., et al. (2021). Response shift in patient-reported outcomes: Definition, theory, and a revised model. Quality of Life Research, 30(12), 3309–3322. https://doi.org/10.1007/s11136-021-02846-wCrossRefPubMedPubMedCentral

Titel: Non-parametric measurement for patient-reported outcomes
Auteur: Jan R. Boehnke
Publicatiedatum: 21-01-2022
Uitgeverij: Springer International Publishing
Gepubliceerd in: Quality of Life Research / Uitgave 1/2022
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI: https://doi.org/10.1007/s11136-021-03073-z

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