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Stefanie A. Wind; Benjamin Lugu – Applied Measurement in Education, 2024
Researchers who use measurement models for evaluation purposes often select models with stringent requirements, such as Rasch models, which are parametric. Mokken Scale Analysis (MSA) offers a theory-driven nonparametric modeling approach that may be more appropriate for some measurement applications. Researchers have discussed using MSA as a…
Descriptors: Item Response Theory, Data Analysis, Simulation, Nonparametric Statistics
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Sinharay, Sandip – Applied Measurement in Education, 2017
Karabatsos compared the power of 36 person-fit statistics using receiver operating characteristics curves and found the "H[superscript T]" statistic to be the most powerful in identifying aberrant examinees. He found three statistics, "C", "MCI", and "U3", to be the next most powerful. These four statistics,…
Descriptors: Nonparametric Statistics, Goodness of Fit, Simulation, Comparative Analysis
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Liang, Tie; Wells, Craig S. – Applied Measurement in Education, 2015
Investigating the fit of a parametric model plays a vital role in validating an item response theory (IRT) model. An area that has received little attention is the assessment of multiple IRT models used in a mixed-format test. The present study extends the nonparametric approach, proposed by Douglas and Cohen (2001), to assess model fit of three…
Descriptors: Nonparametric Statistics, Goodness of Fit, Item Response Theory, Test Format
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Guo, Hongwen; Rios, Joseph A.; Haberman, Shelby; Liu, Ou Lydia; Wang, Jing; Paek, Insu – Applied Measurement in Education, 2016
Unmotivated test takers using rapid guessing in item responses can affect validity studies and teacher and institution performance evaluation negatively, making it critical to identify these test takers. The authors propose a new nonparametric method for finding response-time thresholds for flagging item responses that result from rapid-guessing…
Descriptors: Guessing (Tests), Reaction Time, Nonparametric Statistics, Models
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Wells, Craig S.; Bolt, Daniel M. – Applied Measurement in Education, 2008
Tests of model misfit are often performed to validate the use of a particular model in item response theory. Douglas and Cohen (2001) introduced a general nonparametric approach for detecting misfit under the two-parameter logistic model. However, the statistical properties of their approach, and empirical comparisons to other methods, have not…
Descriptors: Test Length, Test Items, Monte Carlo Methods, Nonparametric Statistics
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Meijer, Rob R.; Sijtsma, Klaas – Applied Measurement in Education, 1995
Methods for detecting item score patterns that are unlikely, given that a parametric item response theory model gives an adequate description of the data or given the responses of other persons in the group, are discussed. The use of person-fit statistics in empirical data analysis is briefly discussed. (SLD)
Descriptors: Identification, Item Response Theory, Nonparametric Statistics, Patterns in Mathematics
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Sijtsma, Klaas, Verweij, Anton C. – Applied Measurement in Education, 1992
Empirical data analysis using the Mokken models of monotone homogeneity and double monotonicity is discussed. Results from the Mokken approach with 3 data sets (for a total of 425 elementary school students) pertaining to transitive interference items are compared to Rasch analysis. (SLD)
Descriptors: Comparative Analysis, Elementary Education, Elementary School Students, Item Response Theory
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Meijer, Rob R.; And Others – Applied Measurement in Education, 1996
Several existing group-based statistics to detect improbable item score patterns are discussed, along with the cut scores proposed in the literature to classify an item score pattern as aberrant. A simulation study and an empirical study are used to compare the statistics and their use and to investigate the practical use of cut scores. (SLD)
Descriptors: Achievement Tests, Classification, Cutting Scores, Identification