Using Multivariate Statistics: Pearson New International Edition

Barbara Tabachnick is Professor Emerita of Psychology at California State University, Northridge, and co-author with Linda Fidell of Using Multivariate Statistics and Experimental Designs Using ANOVA. She has published over 70 articles and technical reports and participated in over 50 professional presentations, many invited. She currently presents workshops in computer applications in univariate and multivariate data analysis and consults in a variety of research areas, including professional ethics in and beyond academia, effects of such factors as age and substances on driving and performance, educational computer games, effects of noise on annoyance and sleep, and fetal alcohol syndrome. She is the recipient of the 2012 Western Psychological Association Lifetime Achievement Award.

In this Section:1. Brief Table of Contents2. Full Table of Contents 1. BRIEF TABLE OF CONTENTS Chapter 1 IntroductionChapter 2 A Guide to Statistical Techniques: Using the BookChapter 3 Review of Univariate and Bivariate StatisticsChapter 4 Cleaning Up Your Act: Screening Data Prior to AnalysisChapter 5 Multiple RegressionChapter 6 Analysis of CovarianceChapter 7 Multivariate Analysis of Variance and CovarianceChapter 8 Profile Analysis: The Multivariate Approach to Repeated MeasuresChapter 9 Discriminant AnalysisChapter 10 Logistic RegressionChapter 11 Survival/Failure AnalysisChapter 12 Canonical CorrelationChapter 13 Principal Components and Factor AnalysisChapter 14 Structural Equation ModelingChapter 15 Multilevel Linear ModelingChapter 16 Multiway Frequency Analysis2. FULL TABLE OF CONTENTS Chapter 1: IntroductionMultivariate Statistics: Why?Some Useful DefinitionsLinear Combinations of VariablesNumber and Nature of Variables to IncludeStatistical PowerData Appropriate for Multivariate StatisticsOrganization of the Book Chapter 2: A Guide to Statistical Techniques: Using the BookResearch Questions and Associated TechniquesSome Further ComparisonsA Decision TreeTechnique ChaptersPreliminary Check of the Data Chapter 3: Review of Univariate and Bivariate StatisticsHypothesis TestingAnalysis of VarianceParameter EstimationEffect SizeBivariate Statistics: Correlation and Regression.Chi-Square Analysis Chapter 4: Cleaning Up Your Act: Screening Data Prior to AnalysisImportant Issues in Data ScreeningComplete Examples of Data Screening Chapter 5: Multiple RegressionGeneral Purpose and DescriptionKinds of Research QuestionsLimitations to Regression AnalysesFundamental Equations for Multiple RegressionMajor Types of Multiple RegressionSome Important Issues.Complete Examples of Regression AnalysisComparison of Programs Chapter 6: Analysis of CovarianceGeneral Purpose and DescriptionKinds of Research QuestionsLimitations to Analysis of CovarianceFundamental Equations for Analysis of CovarianceSome Important IssuesComplete Example of Analysis of CovarianceComparison of Programs Chapter 7: Multivariate Analysis of Variance and CovarianceGeneral Purpose and DescriptionKinds of Research QuestionsLimitations to Multivariate Analysis of Variance and CovarianceFundamental Equations for Multivariate Analysis of Variance and CovarianceSome Important IssuesComplete Examples of Multivariate Analysis of Variance and CovarianceComparison of Programs Chapter 8: Profile Analysis: The Multivariate Approach to Repeated MeasuresGeneral Purpose and DescriptionKinds of Research QuestionsLimitations to Profile AnalysisFundamental Equations for Profile AnalysisSome Important IssuesComplete Examples of Profile AnalysisComparison of Programs Chapter 9: Discriminant AnalysisGeneral Purpose and DescriptionKinds of Research QuestionsLimitations to Discriminant AnalysisFundamental Equations for Discriminant AnalysisTypes of Discriminant AnalysisSome Important IssuesComparison of Programs Chapter 10: Logistic RegressionGeneral Purpose and DescriptionKinds of Research QuestionsLimitations to Logistic Regression AnalysisFundamental Equations for Logistic RegressionTypes of Logistic RegressionSome Important IssuesComplete Examples of Logistic RegressionComparison of Programs Chapter 11: Survival/Failure AnalysisGeneral Purpose and DescriptionKinds of Research QuestionsLimitations to Survival AnalysisFundamental Equations for Survival AnalysisTypes of Survival AnalysisSome Important IssuesComplete Example of Survival AnalysisComparison of Programs Chapter 12: Canonical CorrelationGeneral Purpose and DescriptionKinds of Research QuestionsLimitationsFundamental Equations for Canonical CorrelationSome Important IssuesComplete Example of Canonical CorrelationComparison of Programs Chapter 13: Principal Components and Factor AnalysisGeneral Purpose and DescriptionKinds of Research QuestionsLimitationsFundamental Equations for Factor AnalysisMajor Types of Factor AnalysisSome Important IssuesComplete Example of FAComparison of Programs Chapter 14: Structural Equation ModelingGeneral Purpose and DescriptionKinds of Research QuestionsLimitations to Structural Equation ModelingFundamental Equations for Structural Equations ModelingSome Important IssuesComplete Examples of Structural Equation Modeling Analysis.Comparison of Programs Chapter 15: Multilevel Linear ModelingGeneral Purpose and DescriptionKinds of Research QuestionsLimitations to Multilevel Linear ModelingFundamental EquationsTypes of MLMSome Important IssuesComplete Example of MLMComparison of Programs Chapter 16: Multiway Frequency AnalysisGeneral Purpose and DescriptionKinds of Research QuestionsLimitations to Multiway Frequency AnalysisFundamental Equations for Multiway Frequency AnalysisSome Important IssuesComplete Example of Multiway Frequency AnalysisComparison of Programs