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Penfield, Douglas A.; Koffler, Stephen L. – 1974
Four nonparametric alternatives to the parametric Bartlett test are presented for handling the K-sample equality of variance problem. The two sample Siegel-Tukey Test, Mood Coefficient of Alienation Test, and Klotz Test are extended to the multisample situation by the methods of Puri. A fourth alternative involving a Q-statistic procedure…
Descriptors: Analysis of Variance, Comparative Analysis, Computer Programs, Nonparametric Statistics
Feir, Betty J.; Toothaker, Larry E. – 1974
Researchers are often in a dilemma as to whether parametric or nonparametric procedures should be cited when assumptions of the parametric methods are thought to be violated. Therefore, the Kruskal-Wallis test and the ANOVA F-test were empirically compared in terms of probability of a Type I error and power under various patterns of mean…
Descriptors: Analysis of Variance, Comparative Analysis, Nonparametric Statistics, Sampling

Feir-Walsh, Betty J.; Toothaker, Larry E. – Educational and Psychological Measurement, 1974
Descriptors: Analysis of Variance, Comparative Analysis, Hypothesis Testing, Nonparametric Statistics

Levy, Kenneth J. – Journal of Experimental Education, 1979
Dunnett's procedure for comparing K-1 treatments with a control is discussed within the context of three nonparametric models: those of Kruskal-Wallis, Friedman, and Cochran. (Author/MH)
Descriptors: Analysis of Variance, Comparative Analysis, Mathematical Models, Nonparametric Statistics

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

Bintig, Arnfried – Educational and Psychological Measurement, 1980
Twelve variance-analytical and nonparametrical coefficients of reliability for rating scales designed for rating persons were compared to each other theoretically and empirically. Preference for two coefficients was established. The intraclass correlation coefficient appeared to be useful for the estimation of reliability as well. (Author/RL)
Descriptors: Analysis of Variance, Comparative Analysis, Hypothesis Testing, Mathematical Models
Srisukho, Dirake; Marascuilo, Leonard A. – 1974
Based on a Monte Carlo simulation, this study is designed to investigate the power of the Kruskal-Wallis's H-test compared to the power of the F-test for three equal moderate sample sizes drawn at random from distributions of common or different shapes but for which the population distributions have equal variances. The distributions are the…
Descriptors: Analysis of Variance, Comparative Analysis, Hypothesis Testing, Monte Carlo Methods
Kelley, D. Lynn; And Others – 1994
The Type I error and power properties of the 2x2x2 analysis of variance (ANOVA) and tests developed by McSweeney (1967), Bradley (1979), Harwell-Serlin (1989; Harwell, 1991), and Blair-Sawilowsky (1990) were compared using Monte Carlo methods. The ANOVA was superior under the Gaussian and uniform distributions. The Blair-Sawilowsky test was…
Descriptors: Analysis of Variance, Comparative Analysis, Error of Measurement, Monte Carlo Methods

Adams, David R.; Cousley, Samuel B. – Delta Pi Epsilon Journal, 1977
Application of the Kruskal-Wallis test to survey research problems is discussed as an alternative for the business education researcher in testing questionnaire response differences among three or more independent groups. Problem illustrations and a computer program are included. (MF)
Descriptors: Analysis of Variance, Business Education, Comparative Analysis, Computer Programs
Porter, Andrew C.; McSweeney, Maryellen – 1974
A Monte Carlo technique was used to investigate the small sample goodness of fit and statistical power of several nonparametric tests and their parametric analogues when applied to data which violate parametric assumptions. The motivation was to facilitate choice among three designs, simple random assignment with and without a concomitant variable…
Descriptors: Analysis of Covariance, Analysis of Variance, Comparative Analysis, Goodness of Fit