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Velicer, Wayne F.; Brick, Leslie Ann D.; Fava, Joseph L.; Prochaska, James O. – Multivariate Behavioral Research, 2013
Testing Theory-based Quantitative Predictions (TTQP) represents an alternative to traditional Null Hypothesis Significance Testing (NHST) procedures and is more appropriate for theory testing. The theory generates explicit effect size predictions and these effect size estimates, with related confidence intervals, are used to test the predictions.…
Descriptors: Smoking, Statistical Significance, Confidence Testing, Effect Size
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Ruscio, John; Gera, Benjamin Lee – Multivariate Behavioral Research, 2013
Researchers are strongly encouraged to accompany the results of statistical tests with appropriate estimates of effect size. For 2-group comparisons, a probability-based effect size estimator ("A") has many appealing properties (e.g., it is easy to understand, robust to violations of parametric assumptions, insensitive to outliers). We review…
Descriptors: Psychological Studies, Gender Differences, Researchers, Test Results
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Overall, John E.; Tonidandel, Scott – Multivariate Behavioral Research, 2010
A previous Monte Carlo study examined the relative powers of several simple and more complex procedures for testing the significance of difference in mean rates of change in a controlled, longitudinal, treatment evaluation study. Results revealed that the relative powers depended on the correlation structure of the simulated repeated measurements.…
Descriptors: Monte Carlo Methods, Statistical Significance, Correlation, Depression (Psychology)
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Cramer, Elliot M. – Multivariate Behavioral Research, 1974
Descriptors: Correlation, Matrices, Multiple Regression Analysis, Multivariate Analysis
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Reynolds, Thomas J. – Multivariate Behavioral Research, 1980
Order analysis, a technique to isolate unidimensional hierarchies representing multidimensional structure of binary data, is reviewed. Several theoretical flaws inherent in the probalistic version are presented. Suggestions of possible directions for future research are offered. (Author)
Descriptors: Factor Analysis, Item Analysis, Matrices, Statistical Analysis
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Hakstian, A. Ralph; And Others – Multivariate Behavioral Research, 1980
The procedures yielding confidence intervals for maximized alpha coefficients of Joe and Woodward are reviewed. Confidence interval procedures of Whalen and Masson are next reviewed. Results are then presented of a Monte Carlo investigation of the procedures. (Author/CTM)
Descriptors: Reliability, Research Reviews (Publications), Simulation, Statistical Analysis
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Horn, John L.; Engstrom, Robert – Multivariate Behavioral Research, 1979
Cattell's scree test and Bartlett's chi-square test for the number of factors to be retained from a factor analysis are shown to be based on the same rationale, with the former reflecting subject sampling variability, and the latter reflecting variable sampling variability. (Author/JKS)
Descriptors: Comparative Analysis, Factor Analysis, Hypothesis Testing, Statistical Analysis
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Keselman, H. J. – Multivariate Behavioral Research, 1982
The need for multiple comparison procedures for repeated measures means employing a pooled estimate of error variance to conform to the sphericity assumptions of the design in order to provide a valid test is discussed. An alternative approach which does not require this assumption is presented. (Author/JKS)
Descriptors: Analysis of Variance, Data Analysis, Hypothesis Testing, Research Design
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Hubert, Lawrence J.; Baker, Frank B. – Multivariate Behavioral Research, 1978
The strategy for investigating convergent and discriminant test validity, known as the multitrait-multimethod matrix, is investigated. A nonparametric significance testing procedure is suggested and demonstrated. (JKS)
Descriptors: Correlation, Hypothesis Testing, Mathematical Models, Matrices
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Mendoza, Jorge L.; And Others – Multivariate Behavioral Research, 1974
Descriptors: Comparative Analysis, Hypothesis Testing, Monte Carlo Methods, Research Design
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Takane, 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
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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
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Cohen, Jacob; Nee, John C. M. – Multivariate Behavioral Research, 1990
The analysis of contingency tables via set correlation allows the assessment of subhypotheses involving contrast functions of the categories of the nominal scales. The robustness of such methods with regard to Type I error and statistical power was studied via a Monte Carlo experiment. (TJH)
Descriptors: Computer Simulation, Monte Carlo Methods, Multivariate Analysis, Power (Statistics)
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Cramer, Elliot M. – Multivariate Behavioral Research, 1975
Descriptors: Analysis of Covariance, Comparative Analysis, Discriminant Analysis, Hypothesis Testing
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Wilcox, Rand R. – Multivariate Behavioral Research, 1995
Five methods for testing the hypothesis of independence between two sets of variates were compared through simulation. Results indicate that two new methods, based on robust measures reflecting the linear association between two random variables, provide reasonably accurate control over Type I errors. Drawbacks to rank-based methods are discussed.…
Descriptors: Analysis of Covariance, Comparative Analysis, Hypothesis Testing, Robustness (Statistics)
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