Univariate and Multivariate General Linear Models

Theory and Applications with SAS

Kevin Kim, Neil H. Timm - Collection Statistics: a series of TEXTBOOKS and MONOGRAPHS

550 pages, parution le 31/10/2006 (2^eme édition)

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Résumé

Provides expanded and new material with examples revised to include options available using SAS version 9.0
Presents analyses of simple and complex models, both univariate and multivariate, using data sets from the behavioral sciences
Incorporates recent developments in structural equation modeling, growth mixture modeling, longitudinal data analysis, and hierarchical linear models
Includes a CD-ROM with SAS code and examples

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.

Sommaire

Preface
Overview Of The General Linear Model
Unrestricted General Linear Models
Restricted General Linear Models
Weighted General Linear Models
Multivariate General Linear Models
Mancova Designs
Doubly Multivariate Linear Model
Restricted MGLM And Growth Curve Model
Sur Model And Restricted Gmanova Model
Simultaneous Inference Using Finite Intersection Tests
Computing Power For Univariate And Multivariate GLM
Two-Level Hierarchical Linear Models
Incomplete Repeated Measurement Data
Structural Equation Modeling
References
Author Index
Subject Index

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Chapman and Hall / CRC
Auteur(s)	Kevin Kim, Neil H. Timm
Collection	Statistics: a series of TEXTBOOKS and MONOGRAPHS
Parution	31/10/2006
Édition	2^eme édition
Nb. de pages	550
Format	16 x 24
Couverture	Relié
Poids	899g
Intérieur	Noir et Blanc
EAN13	9781584886341
ISBN13	978-1-58488-634-1