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Showing 1 to 15 of 21 results Save | Export
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Mason, Malia F.; Bar, Moshe – Journal of Experimental Psychology: General, 2012
Mood affects the way people think. But can the way people think affect their mood? In the present investigation, we examined this promising link by testing whether mood is influenced by the presence or absence of associative progression by manipulating the scope of participants' information processing and measuring their subsequent mood. In…
Descriptors: Psychological Patterns, Emotional Response, Influences, Cognitive Processes
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Mair, Patrick; von Eye, Alexander – Psychological Methods, 2007
In this article, the authors have 2 aims. First, hierarchical, nonhierarchical, and nonstandard log-linear models are defined. Second, application scenarios are presented for nonhierarchical and nonstandard models, with illustrations of where these scenarios can occur. Parameters can be interpreted in regard to their formal meaning and in regard…
Descriptors: Hypothesis Testing, Causal Models, Matrices, Coding
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Olejnik, Stephen; Li, Jianmin; Huberty, Carl J.; Supattathum, Suchada – Journal of Educational and Behavioral Statistics, 1997
The difference in statistical power between the original Bonferroni and five modified Bonferroni procedures that control the overall Type I error rate is examined in the context of a correlation matrix where multiple null hypotheses are tested. Power differences of less than 0.05 were typically observed for the modified Bonferroni procedures. (SLD)
Descriptors: Correlation, Hypothesis Testing, Matrices, Power (Statistics)
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Jennrich, Robert I. – Psychometrika, 1978
Under mild assumptions, when appropriate elements of a factor loading matrix are specified to be zero, all orthogonally equivalent matrices differ at most by column sign changes. A variety of results are given here for the more complex case in which the specified values are not necessarily zero. (Author/JKS)
Descriptors: Factor Analysis, Hypothesis Testing, Matrices, Orthogonal Rotation
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Steiger, James H. – Multivariate Behavioral Research, 1980
The goodness-of-fit of correlational pattern hypotheses has traditionally been assessed either with a likelihood ratio statistic or with a quadratic form statistic. Several alternative statistics, based on the use of the Fisher r-to-z transform, are proposed and assessed in a Monte Carlo experiment. (Author/JKS)
Descriptors: Correlation, Data Analysis, Hypothesis Testing, Longitudinal Studies
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Eiting, Mindert H.; Mellenbergh, Gideon J. – Multivariate Behavioral Research, 1981
A commentary is made on a previously published article concerning testing the equivalence of covariance matrices. An error in the previous article (by the same authors) is pointed out and the consequences of the error are discussed. (JKS)
Descriptors: Analysis of Covariance, Data Analysis, Hypothesis Testing, Matrices
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Wallenstein, Sylvan; Fleiss, Joseph L. – Psychometrika, 1979
The multiplicative correction term for the degrees of freedom in a repeated measures analysis of variance table is given for the cases in which there is equal variability per time point, and the correlation between observations is k time units apart. This correction equals the correlation coefficient raised to the kth power. (JKS)
Descriptors: Analysis of Variance, Correlation, Hypothesis Testing, Matrices
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Lance, Charles E. – Multivariate Behavioral Research, 1986
The logic and procedures underlying a disturbance term regression test of logical consistency for structural models are reviewed for recursive and nonrecursive designs. It is shown that in a simple three-variable, complete mediational case the test procedure is mathematically equivalent to a part correlation. (Author/LMO)
Descriptors: Correlation, Hypothesis Testing, Mathematical Models, Matrices
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Ross, Donald C. – Educational and Psychological Measurement, 1983
Theta is a statistic which measures the degree to which a designated pattern successfully partitions a matrix of pre- and post-treatment ratings into regions typical of each of two treatments. In this paper, theta is extended to multivariate and multigroup cases. (Author/BW)
Descriptors: Hypothesis Testing, Matrices, Multivariate Analysis, Research Methodology
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Schurr, K. Terry; Henriksen, L. W. – Educational and Psychological Measurement, 1984
Provided is a description of three methods for testing certain types of a priori hypotheses about differences among covariance matrices. Briefly outlined are procedures for using two computer programs, COFAMM and LISREL, for testing such hypotheses. Also provided are examples of application of the methods to a meaningful data set. (Author/BW)
Descriptors: Analysis of Covariance, Computer Software, Factor Analysis, Hypothesis Testing
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Keselman, H. J.; And Others – Journal of Educational Statistics, 1993
This article shows how a multivariate approximate degrees of freedom procedure based on the Welch-James procedure as simplified by S. Johansen (1980) can be applied to the analysis of repeated measures designs without assuming covariance homogeneity. A Monte Carlo study illustrates the approach. (SLD)
Descriptors: Analysis of Covariance, Equations (Mathematics), Hypothesis Testing, Mathematical Models
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Algina, James; Olejnik, Stephen F. – Educational and Psychological Measurement, 1984
The Welch-James procedure may be used to test hypothesis on means, when independent samples from populations with heterogenous variances are available. Summation formulas for the Welch-James procedure are presented for the 2x2 design. Matrix formulas that permit routine application of the procedure to crossed factorial designs are presented.…
Descriptors: Analysis of Variance, Hypothesis Testing, Mathematical Formulas, Matrices
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Lee, Sik-Yum; Tsui, Kwok-Leung – Psychometrika, 1982
The work of Joreskog and Sorbom in comparing factor structures of several populations is extended to a more general analysis of covariance structures. Also, more complex constraints on parameters are allowed in this work. (JKS)
Descriptors: Analysis of Covariance, Goodness of Fit, Hypothesis Testing, Least Squares Statistics
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Malgady, Robert G.; Huck, Schuyler W. – Educational and Psychological Measurement, 1978
The t ratio used in testing the difference between two independent regression coefficients is generalized to the multivariate case of testing the difference between two vectors of regression coefficients. This is particularly useful in determining which of two variables best predicts a number of criterion variables. (Author/JKS)
Descriptors: Correlation, Hypothesis Testing, Matrices, Multiple Regression Analysis
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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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