Applied Analysis of Variance in Behavioral Science

Overview

Presenting analysis of variance as a research design, a collection of statistical models, an analysis model, and an arithmetic summary of data, this unique new reference offers a selection of the most frequently used designs and techniques and relates them to the social and behavioral sciences.

Covering both theory and applications as well as recent developments in the analysis of variance, Applied Analysis of Variance in Behavioral Science discusses specific designs including ...

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Overview

Presenting analysis of variance as a research design, a collection of statistical models, an analysis model, and an arithmetic summary of data, this unique new reference offers a selection of the most frequently used designs and techniques and relates them to the social and behavioral sciences.

Covering both theory and applications as well as recent developments in the analysis of variance, Applied Analysis of Variance in Behavioral Science discusses specific designs including analysis of covariance, repeated measures design, L square, and confounded factorial designs ... focuses on univariate data with multivariate generalizations ... addresses hierarchical linear models, cell means models, and AVE component estimation ... supplies detailed, step-by-step numerical examples ... explains computer applications using three major software packages ... explores unresolved research questions ... and more!

With over 1300 literature citations, tables, figures, and equations, Applied Analysis of Variance in Behavioral Science is a practical day-to-day guide for psychologists; psychometricians; educational test designers; communications disorders specialists; business, market, and sociological researchers; applied statisticians and biostatisticians; and upper-level undergraduate and graduate students in these disciplines.

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Editorial Reviews

Booknews
A reference devoted to the discussion of analysis of variance (ANOVA) techniques. It presents ANOVA as a research design, a collection of statistical models, an analysis model, and an arithmetic summary of data. Discussion focuses primarily on univariate data, but multivariate generalizations are touched on in several chapters with one chapter specifically dedicated to multivariate analysis of variance (MANOVA). To use the volume most effectively requires knowledge of elementary probability, the power of tests, use of the z-, t-, and F- distributions, and the computational aspects of sums of squares and mean squares. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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Product Details

Table of Contents

"Analysis of Variance Overview, Lynne K. Edwards Multiple Comparisons of Independent Means, Philip H. Ramsey Analysis of Covariance, Scott E. Maxwell, Harold D. Delaney, and Mary F. O'Callaghan Analysis of Repeated Measurements, H. J. Keselman and Joanne C. Keselman Latin Square Designs, John W. Cotton Confounded Factorial Designs, Roger E. Kirk Multivariate Analysis of Variance, Richard J. Harris Unified Power Analysis for t-Tests Through Multivariate Hypotheses, Ralph G. O'Brien and Keith E. Muller Robustness in ANOVA, Rand Wilcox Unbalanced Data and Cell Means Models, Shayle R. Searle Tukey's Nonadditivity Test, Anant M. Kshirsagar Analysis of Time-Dependent Observations, Lynne K. Edwards Hierarchical Linear Models and Experimental Design, Stephen W. Raudenbush Analysis of Categorical Response Variables, Kinley Larntz Variance Component Estimation in Mixed Linear Models, Ronald R. Hocking Some Computer Programs for Selected ANOVA Problems, Lynne K. Edwards and Patricia C. Bland Appendix Table 1: Critical Values of the F Distribution (Random Variable with F Distribution Tabled Value) = Alpha Table 2: Upper Alpha Point of the Studentized Range Distribution with Parameter k and Degrees of Freedom d.f. "

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