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Peer reviewedHettmansperger, Thomas P. – Psychometrika, 1975
Treats the problem of testing an ordered hypothesis based on the ranks of the data. Statistical procedures for the randomized block design with more than one observation per cell are derived. Multiple comparisions and estimation procedures are included. (Author/RC)
Descriptors: Correlation, Data Analysis, Hypothesis Testing, Nonparametric Statistics
Lieberman, Marcus – 1979
This paper illustrates the relevance and utility of non-parametric statistical tests, such as the Kolmogorov-Smirnov two sample test, for analysis of developmental phenomena. This statistic tests the null hypothesis that two samples have been drawn from the same population by comparing their whole distributions, rather than specific parameters and…
Descriptors: Developmental Stages, Nonparametric Statistics, Research Methodology, Research Problems
Killian, C. Rodney; Hoover, H. D. – 1974
The power of the t, expected normal scores, Mann-Whitney U, Tukey, a modified Mann-Whitney U, and an adaptive procedure were investigated when sampling from population models empirically developed from test score distributions. The models used were selected members of the beta family. This investigation was unique in that not only did the means of…
Descriptors: Hypothesis Testing, Investigations, Models, Nonparametric Statistics
Timm, Neil H. – 1974
Multivariate models are demonstrated to analyze repeated measures profile and growth curve data when univariate or multivariate mixed model assumptions are not tenable. Standard mixed model tests are recovered from certain multivariate hypotheses. The procedures are illustrated using numerical examples. (Author/RC)
Descriptors: Hypothesis Testing, Matrices, Models, Nonparametric Statistics
Peer reviewedSchmeidler, James – Educational and Psychological Measurement, 1978
The basic assumption of Cooper's nonparametric test for trend (EJ 125 069) is questioned. It is contended that the proper assumption alters the distribution of the statistic and reduces its usefulness. (JKS)
Descriptors: Analysis of Variance, Hypothesis Testing, Nonparametric Statistics, Research Design
Peer reviewedPenfield, Douglas A. – Educational and Psychological Measurement, 1978
The normal scores test for scale (variance) is presented as an alternative for evaluating the equality of dispersion for two independent populations. Test development is indicated as well as examples illustrating large and small sample situations. Reference is made to comparisons with the F, Mood, and Siegel-Tukey tests. (Author/JKS)
Descriptors: Analysis of Variance, Hypothesis Testing, Mathematical Models, Nonparametric Statistics
Peer reviewedSchulman, Robert S. – Psychometrika, 1978
Ordinal measurement is the rank ordering of individuals in a population. For ordinal measurement, the concept of an individual propensity distribution is his or her true score. Estimation of, as well as other aspects of the distribution, are discussed. (Author/JKS)
Descriptors: Correlation, Measurement, Nonparametric Statistics, Probability
Peer reviewedD'Andrade, Roy G. – Psychometrika, 1978
A monotone invariant method of hierarchical clustering based on the Mann-Whitney U-statistic is presented. The effectiveness of the complete-link, single-link, and U-statistic methods are evaluated. The U-statistic method is found to be consistently more effective in recovering the original tree structures than the alternative methods. (Author/JKS)
Descriptors: Cluster Analysis, Comparative Analysis, Goodness of Fit, Nonparametric Statistics
Stamm, Carol L. – Journal of Physical Education and Recreation, 1976
Use of the coefficient of concordance is explained to be a simple technique for estimating reliability in small scale situation and is advocated as a valuable method for physical educators. (GW)
Descriptors: Measurement Techniques, Nonparametric Statistics, Physical Education, Statistical Analysis
Peer reviewedKingma, Johannes; Reuvekamp, Johan – Educational and Psychological Measurement, 1986
A description of a Mokken test program to test the robustness of nonparametric Stochastic scales is presented. For each sample and the whole population, different scale statistics (both on scale and on item level) are computed recursively. A statistic T is presented for testing the robustness of the scales in the samples. (Author)
Descriptors: Algorithms, Computer Software, Input Output, Mathematical Models
Peer reviewedAiken, Lewis R.; Aiken, Timothy A. – Educational and Psychological Measurement, 1986
Three exact probability tests, counterparts of t tests for single sample, independent samples, and dependent samples, are described for data obtained from ratings on "m" scales by a single rater or on a single scale by "n" raters. (LMO)
Descriptors: Nonparametric Statistics, Probability, Rating Scales, Statistical Distributions
Peer reviewedBoyer, John E., Jr.; And Others – Journal of Educational Statistics, 1983
New tests for comparing the strength of association between a variable and each of two potential predictor variables are proposed and compared to an existing test in a simulation study. Recommendations for use are made. (Author/JKS)
Descriptors: Correlation, Hypothesis Testing, Nonparametric Statistics, Predictive Validity
Leech, Nancy L.; Onwuegbuzie, Anthony J. – 2002
This paper advocates the use of nonparametric statistics. First, the consequence of using parametric inferential techniques under nonnormality is described. Second, the advantages of using nonparametric techniques are presented. The third purpose is to demonstrate empirically how infrequently nonparametric statistics appear in studies, even those…
Descriptors: Classification, Computer Software, Educational Research, Effect Size
Aaron, Bruce C.; Kromrey, Jeffrey D. – 1998
In a Monte Carlo analysis of single-subject data, Type I and Type II error rates were compared for various statistical tests of the significance of treatment effects. Data for 5,000 subjects in each of 6 treatment effect size groups were computer simulated, and 2 types of treatment effects were simulated in the dependent variable during…
Descriptors: Computer Simulation, Effect Size, Monte Carlo Methods, Nonparametric Statistics
Peer reviewedRoberge, James J. – Educational and Psychological Measurement, 1972
Copies of this paper and a source listing which includes input and output data for sample problems can be obtained from the author at Temple University, Philadelphia, Penna. (Author/MB)
Descriptors: Analysis of Variance, Computer Programs, Data Analysis, Nonparametric Statistics


