scholarly journals Range-Preserving Confidence Intervals and Significance Tests for Scalability Coefficients in Mokken Scale Analysis

Author(s):  
Letty Koopman ◽  
Bonne J. H. Zijlstra ◽  
L. Andries van der Ark
2019 ◽  
Vol 44 (3) ◽  
pp. 197-214
Author(s):  
Letty Koopman ◽  
Bonne J. H. Zijlstra ◽  
Mark de Rooij ◽  
L. Andries van der Ark

Two-level Mokken scale analysis is a generalization of Mokken scale analysis for multi-rater data. The bias of estimated scalability coefficients for two-level Mokken scale analysis, the bias of their estimated standard errors, and the coverage of the confidence intervals has been investigated, under various testing conditions. It was found that the estimated scalability coefficients were unbiased in all tested conditions. For estimating standard errors, the delta method and the cluster bootstrap were compared. The cluster bootstrap structurally underestimated the standard errors of the scalability coefficients, with low coverage values. Except for unequal numbers of raters across subjects and small sets of items, the delta method standard error estimates had negligible bias and good coverage. Post hoc simulations showed that the cluster bootstrap does not correctly reproduce the sampling distribution of the scalability coefficients, and an adapted procedure was suggested. In addition, the delta method standard errors can be slightly improved if the harmonic mean is used for unequal numbers of raters per subject rather than the arithmetic mean.


2016 ◽  
Vol 85 ◽  
pp. 65 ◽  
Author(s):  
K.E. Freedland ◽  
M. Lemos ◽  
F. Doyle ◽  
B.C. Steinmeyer ◽  
I. Csik ◽  
...  

2021 ◽  
Vol 8 (3) ◽  
pp. 672-695
Author(s):  
Thomas DeVaney

This article presents a discussion and illustration of Mokken scale analysis (MSA), a nonparametric form of item response theory (IRT), in relation to common IRT models such as Rasch and Guttman scaling. The procedure can be used for dichotomous and ordinal polytomous data commonly used with questionnaires. The assumptions of MSA are discussed as well as characteristics that differentiate a Mokken scale from a Guttman scale. MSA is illustrated using the mokken package with R Studio and a data set that included over 3,340 responses to a modified version of the Statistical Anxiety Rating Scale. Issues addressed in the illustration include monotonicity, scalability, and invariant ordering. The R script for the illustration is included.


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