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Reviewing the theory of the general linear model (GLM) using a
general framework, Univariate and Multivariate General Linear
Models: Theory and Applications with SAS, Second Edition presents
analyses of simple and complex models, both univariate and
multivariate, that employ data sets from a variety of disciplines,
such as the social and behavioral sciences. With revised examples
that include options available using SAS 9.0, this expanded edition
divides theory from applications within each chapter. Following an
overview of the GLM, the book introduces unrestricted GLMs to
analyze multiple regression and ANOVA designs as well as restricted
GLMs to study ANCOVA designs and repeated measurement designs.
Extensions of these concepts include GLMs with heteroscedastic
errors that encompass weighted least squares regression and
categorical data analysis, and multivariate GLMs that cover
multivariate regression analysis, MANOVA, MANCOVA, and repeated
measurement data analyses. The book also analyzes double
multivariate linear, growth curve, seeming unrelated regression
(SUR), restricted GMANOVA, and hierarchical linear models. New to
the Second Edition Two chapters on finite intersection tests and
power analysis that illustrates the experimental GLMPOWER procedure
Expanded theory of unrestricted general linear, multivariate
general linear, SUR, and restricted GMANOVA models to comprise
recent developments Expanded material on missing data to include
multiple imputation and the EM algorithm Applications of MI,
MIANALYZE, TRANSREG, and CALIS procedures A practical introduction
to GLMs, Univariate and Multivariate General Linear Models
demonstrates how to fully grasp the generality of GLMs by
discussing them within a general framework.
Reviewing the theory of the general linear model (GLM) using a
general framework, Univariate and Multivariate General Linear
Models: Theory and Applications with SAS, Second Edition presents
analyses of simple and complex models, both univariate and
multivariate, that employ data sets from a variety of disciplines,
such as the social and behavioral sciences. With revised examples
that include options available using SAS 9.0, this expanded edition
divides theory from applications within each chapter. Following an
overview of the GLM, the book introduces unrestricted GLMs to
analyze multiple regression and ANOVA designs as well as restricted
GLMs to study ANCOVA designs and repeated measurement designs.
Extensions of these concepts include GLMs with heteroscedastic
errors that encompass weighted least squares regression and
categorical data analysis, and multivariate GLMs that cover
multivariate regression analysis, MANOVA, MANCOVA, and repeated
measurement data analyses. The book also analyzes double
multivariate linear, growth curve, seeming unrelated regression
(SUR), restricted GMANOVA, and hierarchical linear models. New to
the Second Edition -Two chapters on finite intersection tests and
power analysis that illustrates the experimental GLMPOWER procedure
-Expanded theory of unrestricted general linear, multivariate
general linear, SUR, and restricted GMANOVA models to comprise
recent developments -Expanded material on missing data to include
multiple imputation and the EM algorithm -Applications of MI,
MIANALYZE, TRANSREG, and CALIS procedures A practical introduction
to GLMs, Univariate and Multivariate General Linear Models
demonstrates how to fully grasp the generality of GLMs bydiscussing
them within a general framework.
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