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Fahoome, Gail; Sawilowsky, Shlomo S. – 2000
Nonparametric procedures are often more powerful than classical tests for real world data, which are rarely normally distributed. However, there are difficulties in using these tests. Computational formulas are scattered throughout the literature, and there is a lack of availability of tables of critical values. This paper brings together the…
Descriptors: Monte Carlo Methods, Nonparametric Statistics, Sample Size, Statistical Distributions
Pyo, Kyong Hyon – 2000
The primary purpose of this study was to compare the performance of three procedures to assess dimensionality that were investigated by R. Nandakumar (1994) at different test conditions to reflect the characteristics of language test data. Procedures investigated were nonlinear factor analysis, the procedure of P. Holland and P. Rosenbaum, and W.…
Descriptors: Evaluation Methods, Factor Analysis, Language Tests, Nonparametric Statistics
Ferrer, Alvaro J. Arce; Wang, Lin – 1999
This study compared the classification performance among parametric discriminant analysis, nonparametric discriminant analysis, and logistic regression in a two-group classification application. Field data from an organizational survey were analyzed and bootstrapped for additional exploration. The data were observed to depart from multivariate…
Descriptors: Classification, Comparative Analysis, Discriminant Analysis, Nonparametric Statistics

Labinowich, Edward P.; Brewer, James K. – Educational and Psychological Measurement, 1971
Descriptors: Analysis of Covariance, Computer Programs, Nonparametric Statistics, Statistical Analysis
Roberge, James J. – Educ Psychol Meas, 1970
A program for calculating Kendall's tau-a, tau-b, partial tau, coefficient of concordance, coefficient of consistence, and coefficient of agreement is presented. In addition, the program provides tests of significance for each of the coefficients except partial tau. (DG)
Descriptors: Computer Programs, Correlation, Nonparametric Statistics, Statistical Analysis

Baker, Frank B. – Journal of Educational Statistics, 1981
The recently developed log-linear model technique for the analysis of contingency tables has many potential applications within educational research. This paper describes the two major models, log-linear and logit-linear, that are employed under this approach. (Author/JKS)
Descriptors: Data Analysis, Goodness of Fit, Nonparametric Statistics, Research Design

Katz, Barry M.; McSweeney, Maryellen – Multivariate Behavioral Research, 1980
An explicit statement of a statistic which is a nonparametric analog to one-way MANOVA is presented. The statistic is a multivariate extension of the nonparametric Kruskal-Wallis test (1952). In addition two post hoc procedures are developed and compared. (Author/JKS)
Descriptors: Analysis of Variance, Data Analysis, Multivariate Analysis, Nonparametric Statistics

Stavig, Gordon; Acock, Alan C. – Educational and Psychological Measurement, 1980
Two r coefficients of association are discussed. One of the coefficients can be applied to any nonparametric test statistic (NTS) in which a normal approximation equation is appropriate. The other coefficient is applicable to any NTS in which exact probabilities are known. (Author/RL)
Descriptors: Comparative Analysis, Correlation, Nonparametric Statistics, Statistical Analysis

Karpman, Mitch – Educational and Psychological Measurement, 1979
This program calculates the chi-square statistic for testing the assumptions of equality and symmetry of covariance matrices in a repeated measures design. (Author)
Descriptors: Analysis of Covariance, Computer Programs, Nonparametric Statistics, Program Descriptions

Zalinski, James; And Others – Educational and Psychological Measurement, 1979
A set of tables for determining tetrachoric correlations is presented. The coefficients have been determined to three-decimal accuracy. (JKS)
Descriptors: Correlation, Expectancy Tables, Nonparametric Statistics, Tables (Data)

Scheiblechner, Hartmann – Psychometrika, 2003
Presented nonparametric tests for testing the validity of polytomous unidimensional ordinal probabilistic polytomous item response theory models along with procedures for testing the comonotonicity of two item sets and for item selection. Describes advantages of the new approach. (SLD)
Descriptors: Item Response Theory, Nonparametric Statistics, Selection, Test Items

Rupp, Andre A. – International Journal of Testing, 2002
Presents an overview of a wide range of measurement models currently available to the analyst who needs to make accurate and valid inferences about respondents and stimuli from data. Reviews models with and without predictor variables or observed and latent predictors, as well as parametric and nonparametric models, and models for order-restricted…
Descriptors: Measurement Techniques, Models, Nonparametric Statistics, Predictor Variables

Hoijtink, Herbert; Molenaar, Ivo W. – Psychometrika, 1997
This paper shows that a certain class of constrained latent class models may be interpreted as a special case of nonparametric multidimensional item response models. Parameters of this latent class model are estimated using an application of the Gibbs sampler, and model fit is investigated using posterior predictive checks. (SLD)
Descriptors: Goodness of Fit, Item Response Theory, Nonparametric Statistics, Prediction

Bolt, Daniel M. – Applied Measurement in Education, 2002
Compared two parametric procedures for detecting differential item functioning (DIF) using the graded response model (GRM), the GRM-likelihood ratio test and the GRM-differential functioning of items and tests, with a nonparametric DIF detection procedure, Poly-SIBTEST. Monte Carlo simulation results show that Poly-SIBTEST showed the least amount…
Descriptors: Comparative Analysis, Item Bias, Monte Carlo Methods, Nonparametric Statistics

Gierl, Mark J.; Bolt, Daniel M. – International Journal of Testing, 2001
Presents an overview of nonparametric regression as it allies to differential item functioning analysis and then provides three examples to illustrate how nonparametric regression can be applied to multilingual, multicultural data to study group differences. (SLD)
Descriptors: Groups, Item Bias, Nonparametric Statistics, Regression (Statistics)