Essence of multivariate thinking : basic themes and methods / Lisa L. Harlow.
Material type:
TextSeries: Multivariate applications book seriesPublication details: New York : Routledge, 2014.Edition: 2nd edDescription: xxxvi, 396 p. : illustrations ; 26 cmISBN: - 9780415873727 (pbk.)
- 000SA.07 23 H286
| 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 |
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| 000SA.07 El37 Joint modeling of longitudinal and time-to-event data / | 000SA.07 H112 Multivariate general linear models / | 000SA.07 H264 Applied multivariate statistical analysis / | 000SA.07 H286 Essence of multivariate thinking : basic themes and methods / | 000SA.07 H641 Modeling count data / | 000SA.07 H873 Theoretical foundations of functional data analysis, with an introduction to linear operators / | 000SA.07 H972 Exploratory multivariate analysis by example using R / |
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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