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Zientek, Linda Reichwein; Thompson, Bruce – Educational Researcher, 2009
Correlation matrices and standard deviations are the building blocks of many of the commonly conducted analyses in published research, and AERA and APA reporting standards recommend their inclusion when reporting research results. The authors argue that the inclusion of correlation/covariance matrices, standard deviations, and means can enhance…
Descriptors: Effect Size, Correlation, Researchers, Multivariate Analysis
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Hsu, Louis M. – Journal of Counseling Psychology, 1989
Discusses three topics related to interpretation of discriminant analyses (DA's): (1) partial F ratios and partial Wilks's lambdas for predictor variables in standard, step-down, and stepwise DA's; (2) relation of goals of classification to definition/evaluation of classification rules; and (3) significance tests for total hit rates in internal…
Descriptors: Data Interpretation, Discriminant Analysis, Multivariate Analysis, Predictor Variables
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Larrabee, Marva J. – Journal of Counseling Psychology, 1982
Presents several multivariate analyses of variance (MANOVA) test procedures. Discusses guidelines for choosing an overall MANOVA test statistic and post hoc tests that determine the dependent variable or variables responsible for any significant effects. Concludes that guidelines based on recent comparisons of the various test statistics be used.…
Descriptors: Discriminant Analysis, Literature Reviews, Multivariate Analysis, Position Papers
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Fok, Lillian Y.; And Others – Journal of Education for Business, 1995
Discusses the nature, power, and limitations of four multivariate techniques: factor analysis, multiple analysis of variance, multiple regression, and multiple discriminant analysis. Shows how decision trees assist in interpreting results. (SK)
Descriptors: Business Administration Education, Data Interpretation, Discriminant Analysis, Factor Analysis