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Peer reviewedMendoza, Jorge L.; And Others – Multivariate Behavioral Research, 1974
Descriptors: Comparative Analysis, Hypothesis Testing, Monte Carlo Methods, Research Design
Peer reviewedGross, Alan L. – Educational and Psychological Measurement, 1975
Describes the MANOVA (multivariate analysis of variance) Computer Program for ascertaining whether k groups differ significantly from one another on p dependent variables. (Author/RC)
Descriptors: Analysis of Variance, Computer Programs, Groups, Hypothesis Testing
Peer reviewedTakane, Yoshio; Cramer, Elliott M. – Multivariate Behavioral Research, 1975
This paper considers the case of two predictor variables. Figures are obtained which show the regions of significance of joint regression coefficients, regression coefficients considered separately, and the multiple correlation. The intersection of these regions of significance and non-significance illustrates how the various apparent…
Descriptors: Correlation, Hypothesis Testing, Maps, Multiple Regression Analysis
Peer reviewedLissitz, Robert W.; Chardos, Steve – Educational and Psychological Measurement, 1975
Describes some of the situations in which a psychologist is likely to violate the assumption of independent errors. A Monte-Carlo study of the effects of this violation is then described. (Author/RC)
Descriptors: Analysis of Variance, Computer Programs, Hypothesis Testing, Matrices
Newman, Isadore; And Others – 1980
When investigating differences between two sets of scores, the t test is appropriate. If the two sets of data are from two groups of subjects, then the independent t test is appropriate. If the two sets are from the same subjects, the dependent t test is required. In this paper, the authors describe the use of a third test when part of a data set…
Descriptors: Hypothesis Testing, Mathematical Models, Multiple Regression Analysis, Research Design
Vitaliano, Peter Paul – 1975
The Cochran Q and the Minimum X sub one squared statistics are two ways to test a hypothesis of equivalent correlated proportions. This study investigated the small sample properties of Q and X sub one squared by Monte Carlo methods. The observed distributions were compared for their rates of covergence to the limiting theoretical X sub one…
Descriptors: Comparative Analysis, Correlation, Hypothesis Testing, Matched Groups
Halperin, Silas – 1976
There are good reasons for the growing popularity of Monte Carlo procedures; but with increasing use comes increasing misuse. A variety of exact and approximate alternatives should be considered before one chooses to approach a problem with Monte Carlo methods. Once it has been decided that simulation is desirable, consideration should be given to…
Descriptors: Computer Programs, Hypothesis Testing, Monte Carlo Methods, Research Methodology
Betz, M. Austin – 1976
Simultaneous test procedures (STPS for short) in the context of the unrestricted full rank general linear multivariate model for population cell means are introduced and utilized to analyze interactions in factorial designs. By appropriate choice of an implying hypothesis, it is shown how to test overall main effects, interactions, simple main,…
Descriptors: Analysis of Variance, Hypothesis Testing, Interaction, Mathematical Models
Tatsuoka, Maurice M. – 1973
A computer-simulated study was made of the sampling distribution of omega squared, a measure of strength of relationship in multivariate analysis of variance which had earlier been proposed by the author. It was found that this measure was highly positively biased when the number of variables is large and the sample size is small. A correction…
Descriptors: Analysis of Variance, Computer Programs, Matrices, Multivariate Analysis
Aiken, Lewis R., Jr. – 1968
The purpose of the Neyman-Johnson statistical technique is to determine a region or span of values on r independent variables where the predicted criterion scores of two or more treatment groups are significantly different. Consequently, the technique should prove especially useful in research concerned with moderator variables or with the…
Descriptors: Educational Research, Interaction, Mathematics, Multiple Regression Analysis
Lord, Frederic M.; Hamilton, Martha S. – 1972
A numerical procedure is outlined for obtaining an interval estimate of true score. The procedure is applied to several sets of test data. (Author)
Descriptors: Bayesian Statistics, Hypothesis Testing, Psychological Testing, Statistical Analysis
Sween, Joyce; Campbell, Donald T. – 1965
The primary purpose of the present study was to investigate the appropriateness of several tests of significance for use with interrupted time series data. The second purpose was to determine what effect the violation of the assumption of uncorrelated error would have on the three tests of significance. The three tests were the Mood test,…
Descriptors: Correlation, Data Analysis, Mathematical Models, Measurement Techniques
Peer reviewedDalton, Starrett; Overall, John E. – Journal of Experimental Education, 1977
A specific form of nonrandom assignment to treatment groups, the "alternate ranks" design, was investigated. This design eliminates the possibility of a correlation between the covariate and the treatment, and rules out experimenter bias in assignment of subjects to groups. (Editor)
Descriptors: Analysis of Covariance, Educational Research, Experimental Groups, Research Methodology
Peer reviewedHamilton, Basil L. – Educational and Psychological Measurement, 1977
The effects of the violation of the assumption of homogeneity of regression on the Type I error rate and on the power of analysis of covariance are investigated. The results indicate that analysis of covariance is robust when sample sizes are equal. (Author/JKS)
Descriptors: Analysis of Covariance, Goodness of Fit, Hypothesis Testing, Multiple Regression Analysis
The Invalidity of Partitioned-U Tests in Canonical Correlation and Multivariate Analysis of Variance
Peer reviewedHarris, Richard J. – Multivariate Behavioral Research, 1976
The partitioned-U procedure is outlined, a fundamental logical flaw in this procedure's avoidance of any direct test of the significance of the first discriminant function or largest coefficient of canonical correlation is pointed out, and two alternatives to the partitioned-U procedure are discussed. (Author/DEP)
Descriptors: Analysis of Variance, Correlation, Hypothesis Testing, Multivariate Analysis


