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Kershner, Keith – 1978
Designed for use with Research for Better Schools' evaluation system, this guide focuses upon basic concepts and statistical procedures applicable to specific research hypotheses emerging from evaluation questions. The first of three sections presents a discussion of descriptive statistics in terms of frequency, central tendency, variability, and…
Descriptors: Career Education, Evaluation, Evaluation Methods, Guides
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Serlin, Ronald C.; Marascuilo, Leonard A. – 1978
When examining a repeated measures design with independent groups for a significant group by trial interaction, classical analysis of variance or multivariate procedures can be used if the assumptions underlying the tests are met. Neither procedure may be justified for designs with small sample sizes and dichotomous dependent variables. An omnibus…
Descriptors: Hypothesis Testing, Mathematical Models, Nonparametric Statistics, Research Design
Pohlmann, John T.; McShane, Michael G. – 1974
The purpose of this paper is to demonstrate the use of the general linear model (GLM) in problems with repeated measures on a dependent variable. Such problems include pretest-posttest designs, multitrial designs, and groups by trials designs. For each of these designs, a GLM analysis is demonstrated wherein full models are formed and restrictions…
Descriptors: Hypothesis Testing, Matrices, Models, Predictor Variables
Wunderlich, Kenneth W.; Borich, Gary D. – 1974
Considerable thought, research, and concern has been expanded in an effort to determine whether the assumption of a quadratic relation between a single predictor and a criterion violated the assumptions which Johnson and Neyman (1936) state for calculating regions of significance about interacting regressions. In particular, there has been special…
Descriptors: Computer Programs, Educational Research, Hypothesis Testing, Mathematical Models
Pravalpruk, Kowit; Porter, Andrew C. – 1974
When random assignment has been accomplished and an analysis of covariance (ANCOVA) is being used to correct for initial differences among treatment groups, use of unreliable covariables not only decreases the power of ANCOVA, but also causes ANCOVA to test biased treatment effects. Several correction procedures have been suggested for the single…
Descriptors: Analysis of Covariance, Mathematical Models, Research Problems, Statistical Analysis
Gullickson, Arlen R.; And Others – 1971
This study is an analysis of the robustness of the Box-Tiao integrated moving averages model for analysis of time series quasi experiments. One of the assumptions underlying the Box-Tiao model is that all N values of alpha subscript t come from the same population which has a variance sigma squared. The robustness was studied only in terms of…
Descriptors: Analysis of Variance, Evaluation Methods, Hypothesis Testing, Mathematical Models
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Huynh, Huynh; Feldt, Leonard S. – Journal of Educational Statistics, 1976
When the variance assumptions of a repeated measures ANOVA are not met, the F distribution of the mean square ratio should be adjusted by the sample estimate of the Box correction factor. An alternative is proposed which is shown by Monte Carlo methods to be less biased for a moderately large factor. (RC)
Descriptors: Analysis of Variance, Computer Programs, Hypothesis Testing, Matrices
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Hsu, Louis M. – Educational and Psychological Measurement, 1978
The problem of determining the significance level which should be used in statistical tests of item validity in order to minimize type I errors is discussed. (Author/JKS)
Descriptors: Hypothesis Testing, Item Analysis, Power (Statistics), Statistical Significance
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Olejnik, Stephen – Journal of Experimental Education, 1987
This study examined the sampling distribution of the analysis of variance F ratio in the two sample cases when it followed a preliminary test for variance equality. When the population variances were equal, the sampling distribution approximated the theoretical F distribution quite well, but not when population variances differed. (JAZ)
Descriptors: Analysis of Variance, Comparative Analysis, Computer Simulation, Sample Size
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Fowler, Robert L. – Educational and Psychological Measurement, 1987
This paper develops a general method for comparing treatment magnitudes for research employing multiple treatment fixed effects analysis of variance designs, which may be used for main effects with any number of levels without regard to directionality. (Author/BS)
Descriptors: Analysis of Variance, Comparative Analysis, Effect Size, Hypothesis Testing
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Olejnik, Stephen F.; Algina, James – Journal of Educational Statistics, 1984
Using computer simulation, parametric analysis of covariance (ANCOVA) was compared to ANCOVA with data transformed using ranks, in terms of proportion of Type I errors and statistical power. Results indicated that parametric ANCOVA was robust to violations of either normality or homoscedasticity, but practiced significant power differences favored…
Descriptors: Analysis of Covariance, Computer Simulation, Hypothesis Testing, Nonparametric Statistics
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Betz, M. Austin; Elliott, Steven D. – Journal of Educational Statistics, 1984
The method of unweighted means in the multivariate analysis of variance with unequal sample sizes was investigated. By approximating the distribution of the hypothesis sums-of-squares-and-cross-products with a Wishart distribution, multivariate test statistics were derived. Monte Carlo methods and a numerical example illustrate the technique.…
Descriptors: Analysis of Variance, Estimation (Mathematics), Hypothesis Testing, Multivariate Analysis
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Levin, Joseph – Multivariate Behavioral Research, 1986
The relation between the power of a significance test in a block design with correlated measurements and the reliability of the measuring instrument is analyzed in terms of the components of variance entering the reliability coefficient and the noncentrality parameter. (Author/LMO)
Descriptors: Analysis of Variance, Hypothesis Testing, Mathematical Models, Power (Statistics)
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Hertzog, Christopher; Rovine, Michael – Child Development, 1985
Attempts to distill a growing technical literature on repeated-measures analysis of variance into a few simple principles for selecting an analytic technique. Argues that researchers ought not opt for a general analysis strategy when current computer technology makes it possible to select the optimal analysis technique for a given data set. (RH)
Descriptors: Analysis of Variance, Computer Software, Developmental Psychology, Hypothesis Testing
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Olejnik, Stephen F. – Journal of Experimental Education, 1984
This paper discusses the sample size problem and four factors affecting its solution: significance level, statistical power, analysis procedure, and effect size. The interrelationship between these factors is discussed and demonstrated by calculating minimal sample size requirements for a variety of research conditions. (Author)
Descriptors: Effect Size, Error of Measurement, Hypothesis Testing, Research Design
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