UID:
almahu_9947367290402882
Umfang:
1 online resource (751 p.)
Ausgabe:
1st ed.
ISBN:
1-281-03372-3
,
9786611033729
,
0-08-053356-6
Inhalt:
Multivariate statistics and mathematical models provide flexible and powerful tools essential in most disciplines. Nevertheless, many practicing researchers lack an adequate knowledge of these techniques, or did once know the techniques, but have not been able to keep abreast of new developments. The Handbook of Applied Multivariate Statistics and Mathematical Modeling explains the appropriate uses of multivariate procedures and mathematical modeling techniques, and prescribe practices that enable applied researchers to use these procedures effectively without needing to concern themsel
Anmerkung:
Description based upon print version of record.
,
Front Cover; HANDBOOK OF APPLIED MULTIVARIATE STATISTICS AND MATHEMATICAL MODELING; Copyright Page; CONTENTS; CONTRIBUTORS; PREFACE; PART I: INTRODUCTION; Chapter 1. Multivariate Statistics and Mathematical Modeling; I. Data Preparation; II. Study Your Data; III. Selecting a Statistical Technique; IV. Data Requirements; V. Interpreting Results; VI. Statistical versus Practical Significance; VII. Overview; References; Chapter 2. Role of Theory and Experimental Design in Multivariate Analysis and Mathematical Modeling; I. The Importance of Theory in Scientific Methodology
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II. The Evolution of Postpositivist Scientific MethodIII. Criticisms of Modern Inductive-Hypothetico-deductive Method; IV. Critical Multiplism (Postpositivist Inductive-Hypothetico-deductive Method); V. Conclusion; References; Chapter 3. Scale Construction and Psychometric Considerations; I. Introduction; II. Scale Definition; III. Scale Construction; IV. Scaling Methods; V. Psychometric Considerations; VI. A Final Word; References; Chapter 4. Interrater Reliability and Agreement; I. Agreement versus Reliability; II. Level of Measurement; III. Type of Replication; IV. Interrater Reliability
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V. Interrater AgreementVI. Summary of Recommendations; References; Chapter 5. Interpreting and Reporting Results; I. Introduction; II. Graphical Displays and Exploratory Data Analysis; III. Contrasts; IV. Interpreting Significance Levels; V. Interpreting the Size of Effects; VI. Understanding Assumptions; VII. Process; VIII. Conclusion; References; PART II: MULTIVARIATE ANALYSIS; Chapter 6. Issues in the Use and Application of Multiple Regression Analysis; I. Overview of Multiple Regression; II. Assumptions and Robustness; III. Regression Diagnostics and Transformations
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IV. Interactions and Moderator EffectsV. Sample Size Requirements for Multiple Regression Analyses; VI. Handling Missing Data; VII. Conclusion; References; Chapter 7. Multivariate Analysis of Variance and Covariance; I. Overview; II. Purpose of Multivariate Analysis of Variance; III. Design; IV. Analysis Guidelines; V. Recommended Practices; References; Chapter 8. Discriminant Analysis; I. Introduction; II. Illustrative Example; III. Descriptive Discriminant Analysis; IV. Predictive Discriminant Analysis; V. Other Issues and Concerns; VI. Conclusion; References
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Chapter 9. Canonical Correlation AnalysisI. Appropriate Research Settings; II. General Taxonomy of Relationship Statistics; III. How Relations Are Expressed; IV. Tests of Significance; V. Variance Accounted for-Redundancy; VI. Interpreting the Components or Variates; VII. Methodological Issues in Canonical Analysis; VIII. Concluding Remarks; References; Chapter 10. Exploratory Factor Analysis; I. Exploratory Factor Analysis; II. Factor Analysis and Principal Components; III. Estimating the Parameters; IV. Standard Errors for Parameter Estimates; V. Target Rotation; VI. Case Study
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VII. Summary
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English
Weitere Ausg.:
ISBN 0-12-691360-9
Sprache:
Englisch
