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Hemker, Bas T.; Sijtsma, Klaas; Molenaar, Ivo W.; Junker, Brian W. – Psychometrika, 1997
Stochastic ordering properties are investigated for a broad class of item response theory (IRT) models for which the monotone likelihood ratio does not hold. A taxonomy is given for nonparametric and parametric models for polytomous models based on the hierarchical relationship between the models. (SLD)
Descriptors: Item Response Theory, Mathematical Models, Nonparametric Statistics
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Wilcox, Rand R. – Educational and Psychological Measurement, 2006
Consider the nonparametric regression model Y = m(X)+ [tau](X)[epsilon], where X and [epsilon] are independent random variables, [epsilon] has a median of zero and variance [sigma][squared], [tau] is some unknown function used to model heteroscedasticity, and m(X) is an unknown function reflecting some conditional measure of location associated…
Descriptors: Nonparametric Statistics, Mathematical Models, Regression (Statistics), Probability
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Kraemer, Helena Chmura – Psychometrika, 1981
Asymptotic distribution theory of Brogden's form of biserial correlation coefficient is derived and large sample estimates of its standard error obtained. Its relative efficiency to the biserial correlation coefficient is examined. Recommendations for choice of estimator of biserial correlation are presented. (Author/JKS)
Descriptors: Correlation, Error of Measurement, Mathematical Models, Nonparametric Statistics
Mittag, Kathleen Cage – 1993
Most researchers using factor analysis extract factors from a matrix of Pearson product-moment correlation coefficients. A method is presented for extracting factors in a non-parametric way, by extracting factors from a matrix of Spearman rho (rank correlation) coefficients. It is possible to factor analyze a matrix of association such that…
Descriptors: Correlation, Factor Analysis, Heuristics, Mathematical Models
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Chang, Hua-Hua – Psychometrika, 1996
H. H. Chang and W. F. Stout (1993) presented a derivation of the asymptotic posterior normality of the latent trait given examinee responses under nonrestrictive nonparametric assumptions for dichotomous item response (IRT) theory models. This paper presents an extension of their results to polytomous IRT models and defines a global information…
Descriptors: Classification, Equations (Mathematics), Item Response Theory, Mathematical Models
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Harwell, Michael R. – Journal of Experimental Education, 1990
The nonparametric hypothesis-testing model of M. L. Puri and P. K. Sen (1969, 1985) circumvents concerns regarding the inapplicability of nonparametric statistics outside simple cases and the lack of pertinent computer programs. The breadth and flexibility of the model are illustrated with several examples. (TJH)
Descriptors: Educational Research, Hypothesis Testing, Mathematical Models, Nonparametric Statistics
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Follmann, Dean – Psychometrika, 1988
The equivalence between non-parametric marginal logistic models (NMLMs) and a class of discrete marginal logistic models is examined. Parametric models offer some of the advantages of the NMLMs approach, but there are more restrictions on the manifest probabilities. (SLD)
Descriptors: Equations (Mathematics), Estimation (Mathematics), Item Analysis, Mathematical Models
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Sijtsma, Klaas; Meijer, Rob R. – Applied Psychological Measurement, 1992
A method is proposed for investigating the intersection of item response functions in the nonparametric item-response-theory model of R. J. Mokken (1971). Results from a Monte Carlo study support the proposed use of the transposed data matrix H(sup T) as an extension to Mokken's approach. (SLD)
Descriptors: Equations (Mathematics), Item Response Theory, Mathematical Models, Matrices
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Chakraborti, S.; Gibbons, Jean D. – Journal of Experimental Education, 1992
The one-sided problem of comparing treatments with a standard on the basis of data available in the context of a one-way analysis of variance is examined, and the methodology of S. Chakraborti and J. D. Gibbons (1991) is extended to the case of unequal sample sizes. (SLD)
Descriptors: Analysis of Variance, Comparative Analysis, Equations (Mathematics), Mathematical Models
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Ramsay, J. O. – Psychometrika, 1991
Kernel smoothing methods for nonparametric item characteristic curve estimation are reviewed. A simulation with 500 examinees and real data from 3,000 records of the Graduate Record Examination illustrate the rapidity of kernel smoothing. Even when population curves are three-parameter logistic, simulation suggests no loss of efficiency. (SLD)
Descriptors: College Entrance Examinations, Computer Simulation, Efficiency, Equations (Mathematics)
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Zimmerman, Donald W.; Zumbo, Bruno D. – Journal of Experimental Education, 1992
A modified "F" test is derived that includes a correction for nonindependence of between-groups and within-groups sample values in analysis of variance (ANOVA) designs. Computer simulations based on normal and nonnormal distributions illustrate the usefulness of the approach, which was more powerful than conventional within-subjects…
Descriptors: Analysis of Variance, Computer Simulation, Correlation, Mathematical Models
Beasley, T. Mark; Leitner, Dennis W. – 1993
The L statistic of E. B. Page (1963) tests the agreement of a single group of judges with an a priori ordering of alternative treatments. This paper extends the two group test of D. W. Leitner and C. M. Dayton (1976), an extension of the L test, to analyze difference in consensus between two unequally sized groups of judges. Exact critical values…
Descriptors: Comparative Analysis, Equations (Mathematics), Estimation (Mathematics), Evaluators
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Buja, Andreas; Eyuboglu, Nermin – Multivariate Behavioral Research, 1992
Use of parallel analysis (PA), a selection rule for the number-of-factors problem, is investigated from the viewpoint of permutation assessment through a Monte Carlo simulation. Results reveal advantages and limitations of PA. Tables of sample eigenvalues are included. (SLD)
Descriptors: Computer Simulation, Correlation, Factor Structure, Mathematical Models
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Chang, Hua-Hua; Stout, William – Psychometrika, 1993
The asymptotic posterior normality of latent variable distributions is established under very general and appropriate hypotheses, providing a probabilistic basis for assessing ability estimation/prediction accuracy in the long test case, as well as a first step in making the Dutch Identity conjecture rigorous. (SLD)
Descriptors: Ability, Bayesian Statistics, Equations (Mathematics), Estimation (Mathematics)
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Stout, William F. – Psychometrika, 1990
Using an infinite item test framework, it is argued that the usual assumption of local independence should be replaced by a weaker assumption--essential independence. The usual assumption of unidimensionality is replaced by a weaker and more appropriate statistically testable assumption of essential unidimensionality. (TJH)
Descriptors: Ability Identification, Equations (Mathematics), Estimation (Mathematics), Item Response Theory
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