Exploratory Mokken Scale Analysis as a Dimensionality Assessment Tool

Abstract

The assessment of the number of dimensions and the dimensionality structure of questionnaire data is important in scale evaluation. In this study, the authors evaluate two dimensionality assessment procedures in the context of Mokken scale analysis (MSA), using a so-called fixed lowerbound. The comparative simulation study, covering various theoretically and empirically relevant conditions, indicates that the MSA procedures may result in scales that are inconsistent with the dimensionality of the data set at hand. That is, a single Mokken scale can be multidimensional, and two Mokken scales can pertain to a single dimension. In an illustrative evaluation, MSA using a range of lowerbounds, rather than a fixed lowerbound, was shown to have some benefits, but not to solve all limitations. The results of this study imply that MSA is perfectly suitable to create Mokken scales. However, MSA appears of limited value as a dimensionality assessment method.

Examination of Polytomous Items’ Psychometric Properties According to Nonparametric Item Response Theory Models in Different Test Conditions

“…When SE i values estimated for H i values gathered according to MHM, belonging to items in different test conditions were examined, these values decreased as sample size increased. This finding bears similarity to that of studies conducted by Smits, Timmerman, and Meijer (2012) and Kogar (2015). Moreover, SE i values from skewed distributions were higher than SE i values from normal distributions.…”

“…SE i values obtained for tests decreased with increased sample size and number of items. This finding resembled that of studies conducted by Smits et al (2012) and Kogar (2015).…”

Item distribution, internal consistency, and structural validity of the German version of the DEMQOL and DEMQOL–proxy

“…Such direct comparisons were not performed in our study due to differences in modeling decisions (parallel iterative MSA rather than bifactor modeling). The merits of MSA and bifactor modeling for clarifying multidimensionality are debatable [ 47 , 48 ]. Therefore, more empirical data are needed before definitive recommendations can be made.…”

An Instructional Module on Mokken Scale Analysis

“…In the context of MSA, scalability coefficients have been described as a method for evaluating a variety of measurement properties, including unidimensionality and local independence (Meijer et al., ). However, there is some debate regarding the interpretation of scalability coefficients in dimensionality analyses (e.g., Smits, Timmerman, & Meijer, ). Nonetheless, scalability coefficients are used in practice to evaluate adherence to the MH model in the context of MSA.…”