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Handbook of Multivariate Experimental Psychology John R. Nesselroade

Handbook of Multivariate Experimental Psychology By John R. Nesselroade

Handbook of Multivariate Experimental Psychology by John R. Nesselroade


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Summary

And wherever re for new guidance belongs to many members search deals with integral wholes-in per of the Society of Multivariate Experimental sonalities, processes, and groups-researchers Psychology, but the actual innervation is due will recognize the vast new future that to the skill and endurance of one man, John multivariate methods open up.

Handbook of Multivariate Experimental Psychology Summary

Handbook of Multivariate Experimental Psychology by John R. Nesselroade

When the first edition of this Handbook was fields are likely to be hard reading, but anyone who wants to get in touch with the published in 1966 I scarcely gave thought to a future edition. Its whole purpose was to growing edges will find something to meet his inaugurate a radical new outlook on ex taste. perimental psychology, and if that could be Of course, this book will need teachers. As accomplished it was sufficient reward. In the it supersedes the narrow conceptions of 22 years since we have seen adequate-indeed models and statistics still taught as bivariate staggering-evidence that the growth of a new and ANOV A methods of experiment, in so branch of psychological method in science has many universities, those universities will need become established. The volume of research to expand their faculties with newly trained has grown apace in the journals and has young people. The old vicious circle of opened up new areas and a surprising increase obsoletely trained members turning out new of knowledge in methodology. obsoletely trained members has to be The credit for calling attention to the need recognized and broken. And wherever re for new guidance belongs to many members search deals with integral wholes-in per of the Society of Multivariate Experimental sonalities, processes, and groups-researchers Psychology, but the actual innervation is due will recognize the vast new future that to the skill and endurance of one man, John multivariate methods open up.

Table of Contents

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.

Additional information

NLS9781461282327
9781461282327
1461282322
Handbook of Multivariate Experimental Psychology by John R. Nesselroade
New
Paperback
Springer-Verlag New York Inc.
2011-10-12
996
N/A
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