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Levy, Kenneth J. – Educational and Psychological Measurement, 1976
Marascuilo (1966) proposes a chi square analog of Scheffe's multiple comparisons procedure. With respect to pairwise comparisons among k independent correlation coefficients, a multiple range procedure will produce lower critical values than the corresponding chi square values, thereby increasing the power of the resulting tests. Basis of the…
Descriptors: Analysis of Variance, Correlation, Mathematical Models, Statistical Significance
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Kennedy, John J. – Educational and Psychological Measurement, 1970
Descriptors: Analysis of Variance, Correlation, Hypothesis Testing, Probability
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Gocka, Edward F. – Educational and Psychological Measurement, 1974
Focuses on the procedures available for substituting a special predictive coding method for some of the more complex general regression procedures. (Author)
Descriptors: Analysis of Variance, Codification, Correlation, Predictor Variables
Brennan, Robert L.; Light, Richard J. – 1973
Basic to many psychological investigations is the question of agreement between observers who independently categorize people. Several recent studies have proposed measures of agreement when a set of nominal scale categories have been pre-defined and imposed on both observers. This study, in contrast, developes a measure of agreement for settings…
Descriptors: Analysis of Variance, Correlation, Hypothesis Testing, Rating Scales
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Good, Ron – Journal of Research in Science Teaching, 1983
Focuses on Binomial Effect Size Display (a concept helpful in interpreting size of an experimental effect). Suggests that both statistical significance and explained variance be reported in experimental research and that values for the latter concepts can be viewed with a more accurate perspective by using BESD. (Author/JN)
Descriptors: Analysis of Variance, Correlation, Science Education, Statistical Analysis
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Keren, Gideon; Lewis, Charles – Educational and Psychological Measurement, 1979
The importance of measuring the size of an effect for fixed effects factorial analysis of variance designs is emphasized. Technical issues in such measurement are considered and examples are provided. (Author/JKS)
Descriptors: Analysis of Variance, Correlation, Factor Analysis, Hypothesis Testing
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Harris, 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
Sockloff, Alan L. – 1974
An equation was derived to determine the relationship between the pooled within-subgroup r (correlation coefficient) and the r obtained from the total group data. It was, thus, possible to assess the amount of distortion introduced by pooling heterogeneous subgroups. As a basis for deciding whether to pool two subgroups in order to calculate a…
Descriptors: Analysis of Variance, Correlation, Hypothesis Testing, Mathematical Models
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Huberty, Carl J. – Educational and Psychological Measurement, 1983
The basic notion of variability is generalized from a univariate context to a multivariate context using two matrix functions, a determinant, and a trace, yielding a number of alternative multivariate indices of shared variation. Some problems in the interpretation of tests of multivariate hypotheses are reviewed. (Author/BW)
Descriptors: Analysis of Variance, Correlation, Data Analysis, Hypothesis Testing
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Beckett, James, III; Schucany, William R. – Journal of Educational Statistics, 1979
The determination of a consensus ranking of products based on the rankings of each judge can be accomplished through the use of a Tukey type multiple comparison procedure. The extension to more than two groups is presented as an analysis of concordance table. (Author/CTM)
Descriptors: Analysis of Variance, Correlation, Rating Scales, Reliability
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Carroll, Robert M.; Nordholm, Lena A. – Educational and Psychological Measurement, 1975
Statistics used to estimate the population correlation ratio were reviewed and evaluated. The sampling distributions of Kelly's and Hays' statistics were studied empirically by computer simulation within the context of a three level one-way fixed effects analysis of variance design. (Author/RC)
Descriptors: Analysis of Variance, Bias, Comparative Analysis, Correlation
Thompson, Bruce – 1992
Conventional statistical significance tests do not inform the researcher regarding the likelihood that results will replicate. One strategy for evaluating result replication is to use a "bootstrap" resampling of a study's data so that the stability of results across numerous configurations of the subjects can be explored. This paper…
Descriptors: Analysis of Covariance, Analysis of Variance, Correlation, Discriminant Analysis
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
Knapp, Thomas R.; Schafer, William D. – 1971
Two theorems concerning F in analysis of covariance with two groups (experimental and control) and one covariable (pretest score) are presented. The first shows explicitly that F is a direct function of the ratio of the variance about the regression line for the total sample to the variance about the within-group regression line. The second…
Descriptors: Analysis of Covariance, Analysis of Variance, Correlation, Multiple Regression Analysis
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Smith, Richard L.; And Others – Educational and Psychological Measurement, 1992
Different approaches to defining suppression in multiple regression/correlation are compared, and their differences are illustrated. A test for determining the significance of a suppressor effect, which is based on the definition of suppression of W. F. Velicer, is extended to the general multiple predictor case and analysis of variance. (SLD)
Descriptors: Analysis of Variance, Comparative Analysis, Correlation, Definitions
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