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Multivariate Data Analysis

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ISBN-10: 0130329290

ISBN-13: 9780130329295

Edition: 6th 2006 (Revised)

Authors: Joseph F. Hair, Ronald L. Tatham, Rolph E. Anderson, William C. Black, Barry J. Babin

List price: $223.20
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Description:

For graduate-level courses in Marketing Research, Research Design and Data Analysis. Multivariate Data Analysis provides an applications-oriented introduction to multivariate data analysis for the nonstatistician by focusing on the fundamental concepts that affect the use of specific techniques.
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Book details

List price: $223.20
Edition: 6th
Copyright year: 2006
Publisher: Prentice Hall PTR
Publication date: 10/28/2005
Binding: Hardcover
Pages: 928
Size: 8.25" wide x 10.00" long x 1.25" tall
Weight: 1.034
Language: English

Preface
Introduction
What Is Multivariate Analysis?
Multivariate Analysis in Statistical Terms
Some Basic Concepts of Multivariate Analysis
A Classification of Multivariate Techniques
Types of Multivariate Techniques
Guidelines for Multivariate Analyses and Interpretation
A Structured Approach to Multivariate Model Building
Databases
Organization of the Remaining Chapters
Summary
Questions
Suggested Readings
References
Preparing for a Multivariate Analysis
Examining Your Data
Introduction
Graphical Examination of the Data
Missing Data
Outliers
Testing the Assumptions of Multivariate Analysis
Incorporating Nonmetric Data with Dummy Variables
Summary
Questions
Suggested Readings
References
Factor Analysis
What Is Factor Analysis?
A Hypothetical Example of Factor Analysis
Factor Analysis Decision Process
An Illustrative Example
Summary
Questions
Suggested Readings
References
Dependence Techniques
Multiple Regression Analysis
What Is Multiple Regression Analysis?
An Example of Simple and Multiple Regression
A Decision Process for Multiple Regression Analysis
Objectives of Multiple Regression
Research Design of a Multiple Regression Analysis
Assumptions in Multiple Regression Analysis
Estimating the Regression Model and Assessing Overall Model Fit
Interpreting the Regression Variate
Validation of the Results
Illustration of a Regression Analysis
Summary
Questions
Suggested Readings
References
Multiple Discriminant Analysis and Logistic Regression
What Are Discriminant Analysis and Logistic Regression?
Analogy with Regression and MANOVA
Hypothetical Example of Discriminant Analysis
The Decision Process for Discriminant Analysis
Objectives of Discriminant Analysis
Research Design for Discriminant Analysis
Assumptions of Discriminant Analysis
Estimation of the Discriminant Model and Assessing Overall Fit
Interpretation of the Results
Validation of the Results
A Two-Group Illustrative Example
A Three-Group Illustrative Example
Logistic Regression: Regression with a Binary Dependent Variable
An Illustrative Example of Logistic Regression
Summary
Questions
Suggested Readings
References
Multivariate Analysis of Variance
MANOVA: Extending Univariate Methods for Assessing Group Differences
A Hypothetical Illustration of MANOVA
A Decision Process for MANOVA
Objectives of MANOVA
Issues in the Research Design of MANOVA
Assumptions of ANOVA and MANOVA
Estimation of the MANOVA Model and Assessing Overall Fit
Interpretation of the MANOVA Results
Validation of the Results
Summary
Illustration of a MANOVA Analysis
Difference Between Two Independent Groups
Difference Between K Independent Groups
A Factorial Design for MANOVA with Two Independent Variables
A Managerial Overview of the Results
Summary
Questions
Suggested Readings
References
Conjoint Analysis
What Is Conjoint Analysis?
A Hypothetical Example of Conjoint Analysis
The Managerial Uses of Conjoint Analysis
Comparing Conjoint Analysis with Other Multivariate Methods
Designing a Conjoint Analysis Experiment
The Objectives of Conjoint Analysis
The Design of a Conjoint Analysis
Assumptions of Conjoint Analysis
Estimating the Conjoint Model and Assessing Overall Fit
Interpreting the Results
Validation of the Conjoint Results
Managerial Applications of Conjoint Analysis
Alternative Conjoint Methodologies
An Illustration of Conjoint Analysis
Summary
Questions
Suggested Readings
References
Interdependence Techniques
Cluster Analysis
What Is Cluster Analysis?
How Does Cluster Analysis Work?
Cluster Analysis Decision Process
Summary of the Decision Process
An Illustrative Example
Summary
Questions
Suggested Readings
References
Multidimensional Scaling and Correspondence Analysis
What Is Multidimensional Scaling?
A Simplified Look at How MDS Works
Comparing MDS to Other Interdependence Techniques
A Decision Framework for Perceptual Mapping
Objectives of MDS
Research Design of MDS
Assumptions of MDS Analysis
Deriving the MDS Solution and Assessing Overall Fit
Interpreting the MDS Results
Validating the MDS Results
Overview of Multidimensional Scaling
Correspondence Analysis
Illustrations of MDS and Correspondence Analysis
Summary
Questions
Suggested Readings
References
Moving Beyond the Basic Techniques
Structural Equation Modeling: An Introduction
What Is Structural Equation Modeling?
SEM and Other Multivariate Techniques
The Role of Theory in Structural Equation Modeling
The History of SEM
A Simple Example of SEM
Developing a Modeling Strategy
Six Stages in Structural Equation Modeling
Summary
Questions
Suggested Readings
Estimating Relationships Using Path Analysis
SEM Abbreviations
Detail on Selected GOF Indices
References
SEM: Confirmatory Factor Analysis
What Is Confirmatory Factor Analysis?
SEM Stages for Testing Measurement Theory Validation with CFA
CFA Illustration
Advanced Topics in CFA
Advanced CFA Illustrations
Summary
Questions
Suggested Readings
Specification Issues in SEM Programs
Measured Variable and Construct Intercept Terms
References
SEM: Testing a Structural Model
What Is a Structural Model?
A Simple Example of a Structural Model
An Overview of Theory Testing with SEM
Stages in Testing Structural Theory
SEM Illustration
Advanced Topics
Summary
Questions
Suggested Readings
The Multivariate Relationships in SEM
How to Fix Factor Loadings to a Specific Value in LISREL
Changing a CFA Setup in LISREL to a Structural Model Test
HBAT Example SEM Program Syntax for LISREL
References
Index