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Nonparametric Evidence of Validity, Reliability, and Fairness for Rater‐Mediated Assessments: An Illustration Using Mokken Scale Analysis
Author(s) -
Wind Stefanie A.
Publication year - 2019
Publication title -
journal of educational measurement
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.917
H-Index - 47
eISSN - 1745-3984
pISSN - 0022-0655
DOI - 10.1111/jedm.12222
Subject(s) - nonparametric statistics , rasch model , item response theory , reliability (semiconductor) , rating scale , parametric statistics , inter rater reliability , scale (ratio) , computer science , econometrics , quality (philosophy) , psychology , level of measurement , psychometrics , statistics , data mining , mathematics , philosophy , epistemology , power (physics) , physics , quantum mechanics
Numerous researchers have proposed methods for evaluating the quality of rater‐mediated assessments using nonparametric methods (e.g., kappa coefficients) and parametric methods (e.g., the many‐facet Rasch model). Generally speaking, popular nonparametric methods for evaluating rating quality are not based on a particular measurement theory. On the other hand, popular parametric methods for evaluating rating quality are often based on measurement theories such as invariant measurement. However, these methods are based on assumptions and transformations that may not be appropriate for ordinal ratings. In this study, I show how researchers can use Mokken scale analysis (MSA), which is a nonparametric approach to item response theory, to evaluate rating quality within the framework of invariant measurement without the use of potentially inappropriate parametric techniques. I use an illustrative analysis of data from a rater‐mediated writing assessment to demonstrate how one can use numeric and graphical indicators from MSA to gather evidence of validity, reliability, and fairness. The results from the analyses suggest that MSA provides a useful framework within which to evaluate rater‐mediated assessments for evidence of validity, reliability, and fairness that can supplement existing popular methods for evaluating ratings.