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Huynh, Huynh – 1977
Three techniques for estimating Kuder Richardson reliability (KR20) coefficients for incomplete data are contrasted. The methods are: (1) Henderson's Method 1 (analysis of variance, or ANOVA); (2) Henderson's Method 3 (FITCO); and (3) Koch's method of symmetric sums (SYSUM). A Monte Carlo simulation was used to assess the precision of the three…
Descriptors: Analysis of Variance, Comparative Analysis, Mathematical Models, Monte Carlo Methods
Meredith, Colin – 1979
The problem of determing how many significant discriminant functions are present in a given data set for a one-way, fixed-effects multivariate analysis of variance design is studied using a Monte Carlo procedure. A variety of procedures, including the popular partitioned-U procedure, are compared with respect to their Type I error rates and power…
Descriptors: Analysis of Variance, Hypothesis Testing, Monte Carlo Methods, Research Reports
Peer reviewed Peer reviewed
Levy, Kenneth J. – Journal of Experimental Education, 1978
Monte Carlo techniques were employed to compare the familiar F-test with Welch's V-test procedure for testing hypotheses concerning a priori contrasts among K treatments. The two procedures were compared under homogeneous and heterogeneous variance conditions. (Author)
Descriptors: Analysis of Variance, Comparative Analysis, Hypothesis Testing, Monte Carlo Methods
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
Peer reviewed Peer reviewed
Games, Paul A.; Howell, John F. – Journal of Educational Statistics, 1976
Compares three methods of analyzing pairwise treatment differences in a multi-treatment experiment via computer simulation techniques. Under the equal n condition, the robustness of the conventional Tukey Wholly Significant Difference test (WSD) to heterogeneous variances was contrasted with two alternate techniques. Under unequal n conditions,…
Descriptors: Analysis of Variance, Comparative Analysis, Computer Programs, Hypothesis Testing
Noe, Michael J. – 1976
This study compared three approaches to the two-factor experiment with repeated measures on one factor: (1) the conventional mixed model analysis of variance, (2) the Greenhouse-Geisser conservative analysis of variance, and (3) multivariate extensions of analysis of variance. Computer simulated data were used in a total of 96 sets of covariance…
Descriptors: Analysis of Variance, Comparative Analysis, Computer Programs, Correlation
Neel, John H.; Stallings, William M. – 1974
An influential statistics test recommends a Levene text for homogeneity of variance. A recent note suggests that Levene's test is upwardly biased for small samples. Another report shows inflated Alpha estimates and low power. Neither study utilized more than two sample sizes. This Monte Carlo study involved sampling from a normal population for…
Descriptors: Analysis of Variance, Educational Research, Hypothesis Testing, Monte Carlo Methods
Pohlmann, John T. – 1972
The Monte Carlo method was used, and the factors considered were (1) level of main effects in the population; (2) level of interaction effects in the population; (3) alpha level used in determining whether to pool; and (4) number of degrees of freedom. The results indicated that when the ratio degrees of freedom (axb)/degrees of freedom (within)…
Descriptors: Analysis of Variance, Computer Programs, Factor Analysis, Hypothesis Testing
Corder-Bolz, Charles R. – 1978
A Monte Carlo Study was conducted to evaluate six models commonly used to evaluate change. The results revealed specific problems with each. Analysis of covariance and analysis of variance of residualized gain scores appeared to substantially and consistently overestimate the change effects. Multiple factor analysis of variance models utilizing…
Descriptors: Analysis of Covariance, Analysis of Variance, Comparative Analysis, Hypothesis Testing
Peer reviewed Peer reviewed
Arvey, Richard D.; Lee, JoAnn – Personnel Psychology, 1981
Conducted a Monte Carlo computer simulation of the ANOVA design to detect job differences. The design proved reasonably powerful in detecting differences. A second study used Monte Carlo methods to analyze the viability of techniques for determining job differences. Offers guidelines for selecting statistical techniques. (Author/RC)
Descriptors: Analysis of Variance, Cluster Grouping, Comparative Analysis, Evaluation Methods
Peer reviewed Peer reviewed
Sherman, Charles R. – Psychometrika, 1972
Results provide a first step toward the establishment of guidelines for the experimenter who wishes to use nonmetric multidimensional scaling effectively, especially when an underlying configuration is hypothesized. (Author)
Descriptors: Analysis of Covariance, Analysis of Variance, Evaluation, Goodness of Fit
Robey, Randall R.; Barcikowski, Robert S. – 1986
This paper reports the results of a Monte Carlo investigation of Type I errors in the single group repeated measures design where multiple measures are collected from each observational unit at each measurement occasion. The Type I error of three multivariate tests were examined. These were the doubly multivariate F test, the multivariate mixed…
Descriptors: Analysis of Variance, Behavioral Science Research, Comparative Analysis, Hypothesis Testing