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Nonparametric IRT analysis of Quality-of-Life Scales and its application to the World Health Organization Quality-of-Life Scale (WHOQOL-Bref).

Sijtsma K, Emons WH, Bouwmeester S, Nyklícek I, Roorda LD - Qual Life Res (2008)

Bottom Line: The monotone homogeneity model analysis yielded unidimensional scales for each content domain.Scalability coefficients further showed that some items have limited scalability with respect to the other items in the same scale.The parametric IRT analyses lead to the rejection of some of the items.

View Article: PubMed Central - PubMed

Affiliation: Department of Methodology and Statistics FSW, Tilburg University, PO Box 90153, Tilburg 5000 LE, The Netherlands. k.sijtsma@uvt.nl

ABSTRACT

Background: This study investigates the usefulness of the nonparametric monotone homogeneity model for evaluating and constructing Health-Related Quality-of-Life Scales consisting of polytomous items, and compares it to the often-used parametric graded response model.

Methods: The nonparametric monotone homogeneity model is a general model of which all known parametric models for polytomous items are special cases. Merits, drawbacks, and possibilities of nonparametric and parametric models and available software are discussed. Particular attention is given to the monotone homogeneity model (also known as the Mokken model), and the often-used parametric graded response model.

Results: Data from the WHOQOL-Bref were analyzed using both the monotone homogeneity model and the graded response model. The monotone homogeneity model analysis yielded unidimensional scales for each content domain. Scalability coefficients further showed that some items have limited scalability with respect to the other items in the same scale. The parametric IRT analyses lead to the rejection of some of the items.

Conclusions: The nonparametric monotone homogeneity model is highly suited for data analysis in a health-related quality-of-life context, and the parametric graded response model may add interesting features to measurement provided the model fits the data well.

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Related in: MedlinePlus

Four ISRFs of Item 3 (‘Distraction due to pain?’, from Physical Health and Well Being domain) showing nonsignificant violations of assumption M and rejected by the GRM: (a) Results from MSP (including the ISF); (b) results from Testgraf98 (ISF and confidence envelopes); (c) and results from Multilog7.0 (GRM)
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Fig5: Four ISRFs of Item 3 (‘Distraction due to pain?’, from Physical Health and Well Being domain) showing nonsignificant violations of assumption M and rejected by the GRM: (a) Results from MSP (including the ISF); (b) results from Testgraf98 (ISF and confidence envelopes); (c) and results from Multilog7.0 (GRM)

Mentions: For the physical domain, the first analysis (high accuracy, more risk of bias) revealed four items of which one or more ISRFs showed minor violations of monotonicity, but none of these violations were significant (5% level, one-tailed test, because only sample decreases are tested as violations; increases support monotonicity). The second analysis (more inaccuracy, less bias) revealed that for all seven items one or more ISRFs showed one or more local decreases, but none them were significant. Figure 5a shows the local, nonsignificant decreases in the ISRFs for Item 3 (‘Distraction due to pain?’).Fig. 5


Nonparametric IRT analysis of Quality-of-Life Scales and its application to the World Health Organization Quality-of-Life Scale (WHOQOL-Bref).

Sijtsma K, Emons WH, Bouwmeester S, Nyklícek I, Roorda LD - Qual Life Res (2008)

Four ISRFs of Item 3 (‘Distraction due to pain?’, from Physical Health and Well Being domain) showing nonsignificant violations of assumption M and rejected by the GRM: (a) Results from MSP (including the ISF); (b) results from Testgraf98 (ISF and confidence envelopes); (c) and results from Multilog7.0 (GRM)
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2238782&req=5

Fig5: Four ISRFs of Item 3 (‘Distraction due to pain?’, from Physical Health and Well Being domain) showing nonsignificant violations of assumption M and rejected by the GRM: (a) Results from MSP (including the ISF); (b) results from Testgraf98 (ISF and confidence envelopes); (c) and results from Multilog7.0 (GRM)
Mentions: For the physical domain, the first analysis (high accuracy, more risk of bias) revealed four items of which one or more ISRFs showed minor violations of monotonicity, but none of these violations were significant (5% level, one-tailed test, because only sample decreases are tested as violations; increases support monotonicity). The second analysis (more inaccuracy, less bias) revealed that for all seven items one or more ISRFs showed one or more local decreases, but none them were significant. Figure 5a shows the local, nonsignificant decreases in the ISRFs for Item 3 (‘Distraction due to pain?’).Fig. 5

Bottom Line: The monotone homogeneity model analysis yielded unidimensional scales for each content domain.Scalability coefficients further showed that some items have limited scalability with respect to the other items in the same scale.The parametric IRT analyses lead to the rejection of some of the items.

View Article: PubMed Central - PubMed

Affiliation: Department of Methodology and Statistics FSW, Tilburg University, PO Box 90153, Tilburg 5000 LE, The Netherlands. k.sijtsma@uvt.nl

ABSTRACT

Background: This study investigates the usefulness of the nonparametric monotone homogeneity model for evaluating and constructing Health-Related Quality-of-Life Scales consisting of polytomous items, and compares it to the often-used parametric graded response model.

Methods: The nonparametric monotone homogeneity model is a general model of which all known parametric models for polytomous items are special cases. Merits, drawbacks, and possibilities of nonparametric and parametric models and available software are discussed. Particular attention is given to the monotone homogeneity model (also known as the Mokken model), and the often-used parametric graded response model.

Results: Data from the WHOQOL-Bref were analyzed using both the monotone homogeneity model and the graded response model. The monotone homogeneity model analysis yielded unidimensional scales for each content domain. Scalability coefficients further showed that some items have limited scalability with respect to the other items in the same scale. The parametric IRT analyses lead to the rejection of some of the items.

Conclusions: The nonparametric monotone homogeneity model is highly suited for data analysis in a health-related quality-of-life context, and the parametric graded response model may add interesting features to measurement provided the model fits the data well.

Show MeSH
Related in: MedlinePlus