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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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Liang, Tie; Wells, Craig S.; Hambleton, Ronald K. – Journal of Educational Measurement, 2014
As item response theory has been more widely applied, investigating the fit of a parametric model becomes an important part of the measurement process. There is a lack of promising solutions to the detection of model misfit in IRT. Douglas and Cohen introduced a general nonparametric approach, RISE (Root Integrated Squared Error), for detecting…
Descriptors: Item Response Theory, Measurement Techniques, Nonparametric Statistics, Models
Monroe, Scott; Cai, Li – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2013
In Ramsay curve item response theory (RC-IRT, Woods & Thissen, 2006) modeling, the shape of the latent trait distribution is estimated simultaneously with the item parameters. In its original implementation, RC-IRT is estimated via Bock and Aitkin's (1981) EM algorithm, which yields maximum marginal likelihood estimates. This method, however,…
Descriptors: Item Response Theory, Maximum Likelihood Statistics, Statistical Inference, Models
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Penfield, Randall D. – Applied Psychological Measurement, 2008
The examination of measurement invariance in polytomous items is complicated by the possibility that the magnitude and sign of lack of invariance may vary across the steps underlying the set of polytomous response options, a concept referred to as differential step functioning (DSF). This article describes three classes of nonparametric DSF effect…
Descriptors: Simulation, Nonparametric Statistics, Item Response Theory, Computation
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Ryden, Jesper – International Journal of Mathematical Education in Science and Technology, 2008
Extreme-value statistics is often used to estimate so-called return values (actually related to quantiles) for environmental quantities like wind speed or wave height. A basic method for estimation is the method of block maxima which consists in partitioning observations in blocks, where maxima from each block could be considered independent.…
Descriptors: Simulation, Probability, Computation, Nonparametric Statistics
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Zimmerman, Donald W. – Psicologica: International Journal of Methodology and Experimental Psychology, 2004
It is well known that the two-sample Student t test fails to maintain its significance level when the variances of treatment groups are unequal, and, at the same time, sample sizes are unequal. However, introductory textbooks in psychology and education often maintain that the test is robust to variance heterogeneity when sample sizes are equal.…
Descriptors: Sample Size, Nonparametric Statistics, Probability, Statistical Analysis
Olejnik, Stephen F.; Algina, James – 1986
Sampling distributions for ten tests for comparing population variances in a two group design were generated for several combinations of equal and unequal sample sizes, population means, and group variances when distributional forms differed. The ten procedures included: (1) O'Brien's (OB); (2) O'Brien's with adjusted degrees of freedom; (3)…
Descriptors: Error of Measurement, Evaluation Methods, Measurement Techniques, Nonparametric Statistics
Mandeville, Garrett K.; And Others – 1975
A strategy for comparing two sets of results (one based upon early childhood recollections (ECR) and another upon video taped (VT) group behavior) from the Perceptual Characteristics Rating Scale was developed. The null distribution of the mean deviation was estimated by randomly matching an ECR response vector with a VT response vector. To…
Descriptors: Comparative Analysis, Correlation, Data Analysis, Goodness of Fit