Handbook of multivariate experimental psychology

I Multivariate Method and Theory Construction.- 1 Psychological Theory and Scientific Method.- 1. The Role of Methodology in Science.- 2. Design of This Book.- 3. Some Major Historical Springs of Methodological Tradition.- 4. What Is and What Might Be in Present-Day Research Method Concepts.- 5. The Nature of the Inductive-Hypothetico-Deductive (IHD) Method in Science.- 6. Summary.- References.- 2 The Principles of Experimental Design and Analysis in Relation to Theory Building.- 1. The Six Basic Parameters of Experimental Design.- 2. The Logically Possible and Practically Viable Types of Experimental Design.- 3. The Main Methods of Mathematico-Statistical Treatment.- 4. Definition of Theory, Law, Postulate, Hypothesis, and Reversibility-Irreversibility.- 5. Social and Psychological Influences in the Natural History of Scientific Theory.- 6. The Total Plan: Advantages and Disadvantages Guiding the Choice among Various Research Procedures.- 7. Creative Scientific Thinking in Relation to Multivariate and Bivariate Procedures.- 8. Summary.- References.- 3 The Data Box: Its Ordering of Total Resources in Terms of Possible Relational Systems.- 1. Relational System, Hypothesis, Design, and Method as the Four Panels of the Investigatory Plan.- 2. The Purpose of Developing the Covariation Chart into the BDRM or Data Box.- 3. Two Protoconstructs: Pattern Entity (Vector) and Attribute Scale (Scalar).- 4. The Ten Coordinates of the Hyperspace BDRM.- 5. The Nature and Definition of a BDRM Facet.- 6. Principles Governing "Entries": Aspects and Shifts.- 7. The Numbers and Varieties of Facets, and Associated Techniques.- 8. The Numbers and Varieties of Faces, Frames, and Grids.- 9. The Totality of Possible Direct and Derived Relational Analyses and Techniques.- 10. Sources of Variance and Covariance in the Data Box: Observable and Inherent (Ideal, Conceptual) Sources Contrasted.- 11. Scales and Standardizations: Normative, Ipsative, Abative.- 12. Superordinate Relational and Interactional Analysis Techniques: Including Superset and Interset Factor Analysis.- 13. Summary, Glossary, and Notation.- References.- 4 The Meaning and Strategic Use of Factor Analysis.- 1. Its Role and Relationships among Statistical Methods.- 2. The Basic Mathematical Propositions and Formulations.- 3. Alternative Models: Components and Factors.- 4. Properties and Formulas for the Full Factor Model.- 5. Unique Resolution and the Tests of Its Attainment.- 6. Factor Invariance, Identification, and Interpretation.- 7. Deciding the Number of Factors.- 8. The Reticular and Strata Models for Higher-Order Factors.- 9. Some Modifications, Developments, and Conditions of the Main Factor Model.- 10. Strategies in the Practical Use of Factor Analysis.- 11. Questions of Statistical Significance and Use of Computer Procedures.- 12. Summary (and Rationale of Notation).- References.- II Multivariate Modeling and Data Analysis.- 5 Analysis of Covariance Structures.- 1. Introduction.- 2. Some Types of Covariance Structures.- 3. General Approaches to Analysis of Covariance Structures.- 4. Analysis of the Examples.- 5. Generalizations.- References.- 6 Exploratory Factor Analysis.- 1. Introduction.- 2. Decision Points in Factoring.- 3. Implications: Some Designs for Exploratory Factor Analysis.- References.- 7 Confirmatory Factor Analysis.- 1. Philosophical Contrasts between Exploratory and Confirmatory Factor Analysis.- 2. The Fundamentals of Confirmatory Factor Analysis.- 3. Applications for Confirmatory Factor Analysis.- 4. Conclusion.- References.- 8 Multimode Factor Analysis.- 1. Multimode Experimental Design.- 2. Factor-Analytic Developments.- 3. Application: Spectrum of Affect.- 4. Comparisons and Contemplations.- References.- 9 Causal Modeling via Structural Equation Systems.- 1. Introduction.- 2. Structural Equations.- 3. Path Diagrams.- 4. Representation Systems.- 5. Estimation Systems.- 6. Examples.- 7. Future Directions.- References.- 10 Multivariate Analysis of Discrete Data.- 1. Introduction.- 2. One-Way Tables.- 3. Bivariate Data: Two-Way Tables.- 4. Multiway Tables.- 5. Latent Structure Models.- 6. Conclusion.- References.- 11 Some Multivariate Developments in Nonparametric Statistics.- 1. A Characterization of Nonparametric Statistics.- 2. Multivariate Perspective.- 3. Exploratory Nonparametric Analysis of All Analytical Units.- 4. Exploratory Nonparametric Analysis of Subsets of Analytical Units.- 5. Confirmatory Nonparametric Analysis.- 6. Discussion and Summary.- References.- 12 Multivariate Analysis of Variance.- 1. Classical Approach.- 2. General Linear Model Approach.- 3. Significance Tests.- 4. Discriminant Analysis.- References.- 13 Multidimensional Scaling.- 1. Introduction.- 2. Models and Methods.- 3. Important Findings.- 4. Classic Problems in MDS.- 5. Current Issues and Future Directions.- References.- 14 The Methods and Problems of Cluster Analysis.- 1. Introduction to Cluster Analysis.- 2. Cluster Analysis Methods.- 3. Similarity.- 4. Unresolved Problems of Cluster Analysis.- 5. Final Remarks.- References.- 15 Human Behavior Genetics.- 1. Introduction.- 2. The Development of Multivariate Human Behavior Genetic Analysis.- 3. Multivariate Generalization of Path Analysis.- 4. Application of Multivariate Path Analysis: Nuclear Family and Twin Design.- 5. Application of Multivariate Path Analysis: Full Adoption Design.- 6. Current Status of Multivariate Human Behavior Genetics.- 7. Multivariate Behavior Genetic Models of Development.- 8. Future Directions: Intergenerational Equilibrium?.- 9. Summary.- References.- 16 Multivariate Reliability Theory: Principles of Symmetry and Successful Validation Strategies.- 1. Introduction.- 2. Basic Concepts of Reliability Theory.- 3. Multivariate Extensions of Reliability Concepts.- 4. Foundations of a General Measurement and Research Strategy Synthesizing the Experimental and the Psychometric Traditions in Psychology.- 5. Paradoxes Revisited.- 6. Relationships to Other Approaches, Implications, and Conclusions.- References.- 17 Dynamic but Structural Equation Modeling of Repeated Measures Data.- 1. Introduction.- 2. Basic Features of a Latent Growth Curve Model.- 3. Dynamic Modeling with Latent Growth Curves.- 4. The Curve-of-Factors Model of Multivariate Growth.- 5. The Factor-of-Curves Model as a Multivariate Alternative.- 6. Discussion of Further Issues.- 7. Appendix: Assorted Technical Issues for LGM Programming.- References.- 18 N-Way Factor Analysis for Obtaining Personality, Situation, and Test Form Contributions to a Psychological Response: Illustrated by a Three-Way Plasmode.- 1. Three Existing Approaches and Two Possible Models for Representing Environment in the Behavioral Equation.- 2. The Utility of Alternative Breakdowns into Contributing Factor Systems.- 3. The Problem of "Side Effects" in Analysis by Faces.- 4. Numerical, Plasmode Illustration.- 5. Summary.- 6. Appendix: Boundary Values.- References.- III Multivariate Research and Theory.- 19 Thinking about Human Abilities.- 1. The Many and Few of Human Abilities: Common and Specific.- 2. A Hierarchy of Human Abilities.- 3. Developmental Evidence.- 4. Genetic Evidence and Early Development.- 5. To Come to a Close.- References.- 20 Personality: Multivariate Systems Theory and Research.- 1. Introduction.- 2. Traits, States, and Situations: An Overview.- 3. Multivariate Personality Research: Some Basic Issues.- 4. Classification of Traits.- 5. Primary Source Traits in L- and Q-Data.- 6. Higher-Order Factors.- 7. Objective Test Data.- 8. The Universality of Source Traits.- 9. The Heritability of Personality.- 10. States and Processes.- 11. The Full Specification Equation.- 12. Conclusion.- 13. Summary.- References.- 21 Elucidation of Motivation Structure by Dynamic Calculus.- 1. Introduction.- 2. Criticisms of Cattell's Motivation Research.- 3. Exploratory Factor-Analytic Principles in Motivation Research.- 4. Objective Devices and the Measurement of Motivation Strength Components.- 5. Dynamic Structure of Ergs and Sentiments.- 6. Computation of Ergic Tension Arousal and Sentiment Activation.- 7. Measurement of Dynamic Motivation Structure.- 8. Dynamic Calculus of Conflict.- 9. Structured Learning Theory of Motivation...- 10. Systems Theory Approach to Motivation.- 11. Summary and Conclusions.- References.- 22 Multivariate Approaches to Human Learning.- 1. Introduction.- 2. Factor Analysis and Learning.- 3. Structured Learning Theory.- 4. Summary.- References.- 23 Clinical Psychology: A Multivariate Appraisal.- 1. Introduction.- 2. Some General Considerations: Developments and Shortcomings of Research in Clinical Psychology.- 3. Selected Topics.- 4. Future Directions.- References.- 24 Psychophysiological Processes.- 1. Introduction.- 2. Patterns of Activation.- 3. Personality Traits.- 4. Psychophysiological Research and Applied Areas.- 5. Essentials of Psychophysiological Assessment.- References.- 25 Organizational Climate.- 1. Introduction.- 2. Toward a Theory of Organizational Climate.- 3. Measurement Problems and Strategies.- 4. Dimensions of Organizational Climate.- 5. Homogeneity of Climate in Complex Organizations.- 6. Types of Organizational Climate.- 7. Prediction of Organizational Performance Criteria.- References.- 26 Multivariate Analyses of the Sociology of Intelligence.- 1. J. B. Mailer: The Sociology of Intelligence in New York, 1930.- 2. C. Burt: Educational Backwardness in London.- 3. E. L. Thorndike: Your City.- 4. K. S. Davenport and H. H. Remmers: Intelligence Differences between the American States.- 5. R. L. Thorndike: More American Cities.- 6. S. Wiseman: The Manchester Studies.- 7. O. D. Duncan: Path Models in Sociology.- 8. R. Lynn: A Path Model of the Sociology of Intelligence in the British Isles.- 9. R. Lynn: The Sociology of Intelligence in France.- 10. Conclusion.- References.