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The Case for Use of Simple Difference Scores to Test the Significance of Differences in Mean Rates of Change in Controlled Repeated Measurements Designs
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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)
A Monte Carlo Comparison of the Univariate and Multivariate Methods for the Groups by Trials Repeated Measures Design.
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Mendoza, Jorge L.; And Others – Multivariate Behavioral Research, 1974
Descriptors: Comparative Analysis, Hypothesis Testing, Monte Carlo Methods, Research Design
Robustness of Type I Error and Power in Set Correlation Analysis of Contingency Tables.
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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)
The Sampling Distribution and a Test for the Significance of the Bimultivariate Redundancy Statistic: A Monte Carlo Study
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Miller, John K. – Multivariate Behavioral Research, 1975
Descriptors: Correlation, Goodness of Fit, Hypothesis Testing, Matrices
A Factorial Evaluation of Effects of Model Specification and Error on Parameter Estimation in a Structural Equation Model.
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Farley, John U.; Reddy, Srinivas K. – Multivariate Behavioral Research, 1987
In an experiment manipulating artificial data in a factorial design, model misspecification and varying levels of error in measurement and in model structure are shown to have significant effects on LISREL parameter estimates in a modified peer influence model. (Author/LMO)
Descriptors: Analysis of Variance, Computer Simulation, Error of Measurement, Estimation (Mathematics)