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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