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Skidmore, Susan Troncoso; Thompson, Bruce – Educational and Psychological Measurement, 2010
The purpose of the present study is to provide a historical account and metasynthesis of which statistical techniques are most frequently used in the fields of education and psychology. Six articles reviewing the "American Educational Research Journal" from 1969 to 1997 and five articles reviewing the psychological literature from 1948 to 2001…
Descriptors: Educational Research, Meta Analysis, Synthesis, Statistical Studies
Fundamentals of Canonical Correlation Analysis: Basics and Three Common Fallacies in Interpretation.
Thompson, Bruce – 1987
Canonical correlation analysis is illustrated and three common fallacious interpretation practices are described. Simply, canonical correlation is an example of the bivariate case. Like all parametric methods, it involves the creation of synthetic scores for each person. It presumes at least two predictor variables and at least two criterion…
Descriptors: Correlation, Multivariate Analysis, Research Problems, Statistical Bias
Thompson, Bruce – 1987
The use of planned, or "a priori," and unplanned, or "post hoc," comparisons to isolate differences among means in analysis of variance research is discussed. Planned comparisons typically involve weighting data by sets of "contrasts." Planned comparison offer more power against Type II errors. In addition, they force…
Descriptors: Analysis of Variance, Research Methodology, Statistical Analysis, Statistical Significance
Thompson, Bruce; Miller, James H. – 1985
Methods of regression commonality analysis are generalized for use in canonical correlation analysis. An actual data set (involving educators' attitudes toward death and age, locus of control, religion, and occupational role in working with terminally ill children) is employed to illustrate the extension. The method can be applied with respect to…
Descriptors: Correlation, Elementary Secondary Education, Multivariate Analysis, Predictor Variables

Thompson, Bruce – 1989
In the present study Monte Carlo methods were employed to evaluate the degree to which canonical function and structure coefficients may be differentially sensitive to sampling error. Sampling error influences were investigated across variations in variable and sample (n) sizes, and across variations in average within-set correlation sizes and in…
Descriptors: Computer Simulation, Correlation, Monte Carlo Methods, Multivariate Analysis

Thompson, Bruce; Borrello, Gloria M. – Educational and Psychological Measurement, 1985
Multiple regression analysis is frequently being employed in experimental and non-experimental research. However, when data include predictor variables that are correlated, some regression results can become difficult to interpret. This paper presents a study to provide a demonstration that structure coefficients may be useful in these cases.…
Descriptors: Correlation, Multiple Regression Analysis, Multivariate Analysis, Predictor Variables

Thompson, Bruce – Educational and Psychological Measurement, 1986
This paper reports a Monte Carlo study of differences induced by different analysis choices over selected types of aptitude treatment interaction (ATI) data (nine combinations of three sample sizes and three population parameter effect sizes). Generally, ANOVA methods tended to overestimate smaller effect sizes and to underestimate larger effect…
Descriptors: Analysis of Variance, Aptitude Treatment Interaction, Effect Size, Monte Carlo Methods
Thompson, Bruce – 1985
Hypothetical data sets are used to demonstrate how canonical correlation methods subsume other commonly utilized parametric methods. Analysis of variance, analysis of covariance, multiple analysis of variance, and multiple analysis of covariance are heavily used by educational researchers. It is concluded that researchers would do well to consider…
Descriptors: Analysis of Covariance, Analysis of Variance, Comparative Analysis, Correlation
Thompson, Bruce – 1994
The present paper suggests that multivariate methods ought to be used more frequently in behavioral research and explores the potential consequences of failing to use multivariate methods when these methods are appropriate. The paper explores in detail two reasons why multivariate methods are usually vital. The first is that they limit the…
Descriptors: Analysis of Covariance, Behavioral Science Research, Causal Models, Correlation