Using R With Multivariate Statistics

Dr. Randall E. Schumacker is professor of educational research at the University of Alabama. He has written and co-edited several books, including A Beginner’s Guide to Structural Equation Modeling, Third Edition, Advanced Structural Equation Modeling: Issues and Techniques, Interaction and Non-Linear Effects in Structural Equation Modeling, New Developments and Techniques in Structural Equation Modeling, Understanding Statistical Concepts Using S-PLUS, Understanding Statistics Using R, and Learning Statistics Using R.  Dr. Schumacker was the founder and is now emeritus editor of Structural Equation Modeling: A Multidisciplinary Journal, and has established the Structural Equation Modeling Special Interest Group within the American Educational Research Association (AERA). He is also the emeritus editor of Multiple Linear Regression Viewpoints, the oldest journal sponsored by AERA (Multiple Linear Regression: General Linear Model Special Interest Group). Dr. Schumacker has conducted international and national workshops, has served on the editorial board of several journals, and currently pursues his research interests in statistics and structural equation modeling. He was the 1996 recipient of the Outstanding Scholar Award and the 1998 recipient of the Charn Oswachoke International Award. In 2010, he launched the DecisionKit App for the iPhone, iPad, and iTouch, which can assist researchers in making decisions about which measurement, research design, or statistic to use in their research projects. In 2011, he received the Apple iPad Award. In, 2012, he received the CIT Faculty Technology Award. In 2013, he received the McCrory Faculty Excellence in Research Award from the College of Education at the University of Alabama. In 2014, Dr. Schumacker was the recipient of the Structural Equation Modeling Service Award at AERA.

• PrefaceAcknowledgmentsAbout the Author1. Introduction and OverviewBackgroundPersons of InterestFactors Affecting StatisticsR SoftwareWeb ResourcesReferences2. Multivariate Statistics: Issues and AssumptionsIssuesAssumptionsSPSS CheckSummaryWeb ResourcesReferences3. Hotelling’s T2 : A Two-Group Multivariate AnalysisOverviewAssumptionsUnivariate Versus Multivariate HypothesisPractical Examples Using RPower and Effect SizeReporting and InterpretingSummaryExercisesWeb ResourcesReferences4. Multivariate Analysis of VarianceMANOVA AssumptionsMANOVA Example: One-Way DesignMANOVA Example: Factorial DesignEffect SizeReporting and InterpretingSummaryExercisesWeb ResourcesReferences5. Multivariate Analysis of CovarianceAssumptionsMultivariate Analysis of CovarianceReporting and InterpretingPropensity Score MatchingSummaryWeb ResourcesReferences6. Multivariate Repeated MeasuresAssumptionsAdvantages of Repeated Measure DesignMultivariate Repeated Measure ExamplesReporting and Interpreting ResultsSummaryExercisesWeb ResourcesReferences7. Discriminant AnalysisOverviewAssumptionsDichotomous Dependent VariablePolytomous Dependent VariableEffect SizeReporting and InterpretingSummaryExercisesWeb ResourcesReferences8. Canonical CorrelationOverviewAssumptionsR PackagesCanonical Correlation ExampleEffect SizeReporting and InterpretingSummaryExercisesWeb ResourcesReferences9. Exploratory Factor AnalysisOverviewTypes of Factor AnalysisAssumptionsFactor Analysis Versus Principal Components AnalysisEFA ExampleReporting and InterpretingSummaryExercisesWeb ResourcesReferencesAppendix: Attitudes Toward Educational Research Scale10. Principal Components AnalysisOverviewAssumptionsBasics of Principal Components AnalysisPrincipal Component ExampleReporting and InterpretingSummaryExercisesWeb ResourcesReferences11. Multidimensional ScalingOverviewAssumptionsR PackagesGoodness-of-Fit IndexMDS Metric ExampleMDS Nonmetric ExampleReporting and Interpreting ResultsSummaryExercisesWeb ResourcesReferences12. Structural Equation ModelingOverviewAssumptionsEqual Variance-Covariance MatricesCorrelation Versus Covariance MatrixR PackagesCFA ModelsStructural Equation ModelsReporting and Interpreting ResultsSummaryExercisesWeb ResourcesReferencesStatistical TablesTable 1: Areas Under the Normal Curve (z Scores)Table 2: Distribution of t for Given Probability LevelsTable 3: Distribution of r for Given Probability LevelsTable 4: Distribution of Chi-Square for Given Probability LevelsTable 5: The F Distribution for Given Probability Levels (.05 Level)Table 6: The Distribution of F for Given Probability Levels (.01 Level)Table 7: Distribution of Hartley F for Given Probability LevelsChapter AnswersR Installation and UsageR Packages, Functions, Data Sets, and Script FilesIndex

"This book is not only an excellent introductory resource of multivariate statistics using R, but also provides a complete coverage of multivariate statistics. I really love this book and look forward to using it for my stats courses."