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Essence of multivariate thinking : basic themes and methods / Lisa L. Harlow.

By: Material type: TextTextSeries: Multivariate applications book seriesPublication details: New York : Routledge, 2014.Edition: 2nd edDescription: xxxvi, 396 p. : illustrations ; 26 cmISBN:
  • 9780415873727 (pbk.)
Subject(s): DDC classification:
  • 000SA.07 23 H286
Contents:
Part I: Overview 1. Introduction and Multivariate Themes 2. Background Considerations Part II: Intermediate multivariate Methods with one Continuous Outcome 3. Multiple Regression 4. Analysis of Covariance Part III: Multivariate group methods with categorical variable(s) 5. Multivariate analysis of variance 6. Discriminant Function Analysis 7. Logistic Regression Part IV: Multivatiate Mode3ling Methods 8. Multi-level Modeling 9. Principal Components and Factor Analysis Part V: Structural Equation Modeling 10. Structural Equation Modeling Overview 11. Path Analysis 12. Confirmatory Factor Analysis 13. Latent Variable Modeling Part VI: Summary 14. Integration of Multivariate Methods Appendix A Codebook for Data Used in Example Appendix B Matrices and Multivariate Methods Author index. Subject index.
Summary: By focusing on underlying themes, this book helps readers better understand the connections between multivariate methods. For each method the author highlights: the similarities and differences between the methods, when they are used and the questions they address, the key assumptions and equations, and how to interpret the results.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books ISI Library, Kolkata 000SA.07 H286 (Browse shelf(Opens below)) Available 135533
Total holds: 0

Includes bibliographical references and indexes.

Part I: Overview
1. Introduction and Multivariate Themes
2. Background Considerations

Part II: Intermediate multivariate Methods with one Continuous Outcome
3. Multiple Regression
4. Analysis of Covariance

Part III: Multivariate group methods with categorical variable(s)
5. Multivariate analysis of variance
6. Discriminant Function Analysis
7. Logistic Regression

Part IV: Multivatiate Mode3ling Methods
8. Multi-level Modeling
9. Principal Components and Factor Analysis

Part V: Structural Equation Modeling
10. Structural Equation Modeling Overview
11. Path Analysis
12. Confirmatory Factor Analysis
13. Latent Variable Modeling

Part VI: Summary
14. Integration of Multivariate Methods
Appendix A Codebook for Data Used in Example
Appendix B Matrices and Multivariate Methods

Author index.
Subject index.

By focusing on underlying themes, this book helps readers better understand the connections between multivariate methods. For each method the author highlights: the similarities and differences between the methods, when they are used and the questions they address, the key assumptions and equations, and how to interpret the results.

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