Testing Research Hypotheses with the General Linear Model

Testing Research Hypotheses with the General Linear Model
Author: Keith A. McNeil
Publisher: SIU Press
Total Pages: 400
Release: 1996
Genre: Mathematics
ISBN: 9780809320196

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Briefly describes 777 serial bibliographies relating to modern literature in most of the major languages. Chapters cover comprehensive bibliographies, those for English and foreign literatures, for topics from African American studies to women's studies, and for particular authors. The 1982 edition has been updated and expanded to include information on electronic serial bibliographies. Paper edition (unseen), $19.75. Annotation copyright by Book News, Inc., Portland, OR

Designing General Linear Models to Test Research Hypotheses

Designing General Linear Models to Test Research Hypotheses
Author: Keith A. McNeil
Publisher:
Total Pages: 0
Release: 2012
Genre: Linear models (Statistics)
ISBN: 9780761857686

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The authors discuss General Linear Models specifically designed to statistically test research hypotheses that deal with the differences among group means, relationships between continuous variables, analysis of covariance, interaction effects, nonlinear relationships, and repeated measures. Illustrations of the various analyses using Microsoft Excel and SPSS for Windows are presented.

Sample Size Choice

Sample Size Choice
Author: Robert E. Odeh
Publisher: CRC Press
Total Pages: 218
Release: 2020-08-12
Genre: Mathematics
ISBN: 1000147924

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A guide to testing statistical hypotheses for readers familiar with the Neyman-Pearson theory of hypothesis testing including the notion of power, the general linear hypothesis (multiple regression) problem, and the special case of analysis of variance. The second edition (date of first not mentione

Testing Research Hypotheses Using Multiple Linear Regression

Testing Research Hypotheses Using Multiple Linear Regression
Author: Keith A. McNeil
Publisher:
Total Pages: 616
Release: 1975
Genre: Mathematics
ISBN:

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Multiple regression is becomingmore wide­ly used as the statistical technique for answering research hypotheses. This is so for several reasons: 1) the technique is extreme­ly versatile; 2) the computer has made the technique more available to researchers; and 3) texts such as the authors' earlier work are making the technique more available to re­searchers. The statistical technique of mul­tiple regression allows the inclusion of numerous continuous (quantitative) and categorical (qualitative) variables in the prediction of some criterion. Appendixes contain a multiple regression computer program and data on which the problems are based; a discussion of the simi­larities and differences between analysis of variance and multiple regression; and a computer program providing the regression solution to natural language research hy­potheses.

The Linear Hypothesis

The Linear Hypothesis
Author: George Arthur Frederick Seber
Publisher:
Total Pages: 132
Release: 1980
Genre: Mathematical statistics
ISBN:

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The Linear Model and Hypothesis

The Linear Model and Hypothesis
Author: George Seber
Publisher: Springer
Total Pages: 208
Release: 2015-10-08
Genre: Mathematics
ISBN: 3319219308

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This book provides a concise and integrated overview of hypothesis testing in four important subject areas, namely linear and nonlinear models, multivariate analysis, and large sample theory. The approach used is a geometrical one based on the concept of projections and their associated idempotent matrices, thus largely avoiding the need to involvematrix ranks. It is shown that all the hypotheses encountered are either linear or asymptotically linear, and that all the underlying models used are either exactly or asymptotically linear normal models. This equivalence can be used, for example, to extend the concept of orthogonality to other models in the analysis of variance, and to show that the asymptotic equivalence of the likelihood ratio, Wald, and Score (Lagrange Multiplier) hypothesis tests generally applies.

Multivariate General Linear Models

Multivariate General Linear Models
Author: Richard F. Haase
Publisher: SAGE
Total Pages: 225
Release: 2011-11-23
Genre: Mathematics
ISBN: 1412972493

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This title provides an integrated introduction to multivariate multiple regression analysis (MMR) and multivariate analysis of variance (MANOVA). It defines the key steps in analyzing linear model data and introduces multivariate linear model analysis as a generalization of the univariate model. Richard F. Haase focuses on multivariate measures of association for four common multivariate test statistics, presents a flexible method for testing hypotheses on models, and emphasizes the multivariate procedures attributable to Wilks, Pillai, Hotelling, and Roy.

Parameter Estimation and Hypothesis Testing in Linear Models

Parameter Estimation and Hypothesis Testing in Linear Models
Author: Karl-Rudolf Koch
Publisher: Springer Science & Business Media
Total Pages: 366
Release: 1999-04
Genre: Mathematics
ISBN: 9783540652571

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The necessity to publish the second edition of this book arose when its third German edition had just been published. This second English edition is there fore a translation of the third German edition of Parameter Estimation and Hypothesis Testing in Linear Models, published in 1997. It differs from the first English edition by the addition of a new chapter on robust estimation of parameters and the deletion of the section on discriminant analysis, which has been more completely dealt with by the author in the book Bayesian In ference with Geodetic Applications, Springer-Verlag, Berlin Heidelberg New York, 1990. Smaller additions and deletions have been incorporated, to im prove the text, to point out new developments or to eliminate errors which became apparent. A few examples have been also added. I thank Springer-Verlag for publishing this second edition and for the assistance in checking the translation, although the responsibility of errors remains with the author. I also want to express my thanks to Mrs. Ingrid Wahl and to Mrs. Heidemarlen Westhiiuser who prepared the second edition. Bonn, January 1999 Karl-Rudolf Koch Preface to the First Edition This book is a translation with slight modifications and additions of the second German edition of Parameter Estimation and Hypothesis Testing in Linear Models, published in 1987.