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Principles and Practice of Structural Equation Modeling 3rd edition [Kietas viršelis]

4.11/5 (194 ratings by Goodreads)
  • Formatas: Hardback, 422 pages, aukštis x plotis: 246x174 mm, weight: 956 g
  • Serija: Methodology in the Social Sciences
  • Išleidimo metai: 07-Sep-2010
  • Leidėjas: Guilford Publications
  • ISBN-10: 1606238779
  • ISBN-13: 9781606238776
Kitos knygos pagal šią temą:
  • Formatas: Hardback, 422 pages, aukštis x plotis: 246x174 mm, weight: 956 g
  • Serija: Methodology in the Social Sciences
  • Išleidimo metai: 07-Sep-2010
  • Leidėjas: Guilford Publications
  • ISBN-10: 1606238779
  • ISBN-13: 9781606238776
Kitos knygos pagal šią temą:
This bestselling text provides a balance between the technical and practical aspects of structural equation modeling (SEM). Using clear and accessible language, Rex B. Kline covers core techniques, potential pitfalls, and applications across the behavioral and social sciences. Some more advanced topics are also covered, including estimation of interactive effects of latent variables and multilevel SEM. The companion Web page (please see the books entry at www.guilford.com) offers downloadable syntax, data, and output files for each detailed example for EQS, LISREL, and Mplus, allowing readers to view the results of the same analysis generated by three different computer tools. New to This Edition:





Thoroughly revised and restructured to follow the phases of most SEM analyses Syntax, data, and output files for all detailed research examples are now provided online Exercises with answers, which support self-study Topic boxes on specialized issues, such as dealing with problems in the analysis; the assessment of construct measurement reliability; and more Updated coverage of a more rigorous approach to hypothesis and model testing; the evaluation of measurement invariance; and more.

This book is important reading for graduate students, instructors, and researchers in psychology, education, human development and family studies, management, sociology, social work, nursing, public health, criminal justice, and communication. It also serves as a text for graduate-level courses in structural equation modeling, multivariate statistics, advanced quantitative methods, or research methodology.

Recenzijos

"Kline provides a text that is accessible for graduate students, practitioners, and researchers who are not intimately familiar with SEM techniques. In addition, he effortlessly summarizes current information that researchers who already use SEM should have.A major strength of the book is the individual chapter examples with explanation of the values provided from a variety of statistical analysis packages." - James B. Schreiber, Center for Advancing the Study of Teaching and Learning, Duquesne University, USA

"The coverage is excellent and the writing style is friendly and direct, with a subtle humor that I find refreshing. I especially like the new topic boxes in the third edition, most of which discuss issues that I have had to address separately in lectures." - Jacob Marszalek, Division of Counseling and Educational Psychology, University of MissouriKansas City, USA "Kline provides a text that is accessible for graduate students, practitioners, and researchers who are not intimately familiar with SEM techniques. In addition, he effortlessly summarizes current information that researchers who already use SEM should have.A major strength of the book is the individual chapter examples with explanation of the values provided from a variety of statistical analysis packages." - James B. Schreiber, Center for Advancing the Study of Teaching and Learning, Duquesne University, USA

"The coverage is excellent and the writing style is friendly and direct, with a subtle humor that I find refreshing. I especially like the new topic boxes in the third edition, most of which discuss issues that I have had to address separately in lectures." - Jacob Marszalek, Division of Counseling and Educational Psychology, University of MissouriKansas City, USA

"This is now the #1 book I will recommend to students and substantive researchers (who are not quantitative specialists) who want to learn SEM! Compared to most SEM books that I have seen, this one strikes a better balance between accessibility and breadth. In the third edition, Kline not only has updated the material, but has substantially improved it. " - Noel A. Card, Division of Family Studies and Human Development, University of Arizona, USA

"In the third edition, Kline has improved the pedagogical value of his book relative to prior editions and to other SEM books. The Web page featuring complete computer syntax and data for the examples is very helpful. Other new material further supports a readers understanding of SEM." - Craig Wells, School of Education, University of Massachusetts-Amherst, USA

"Of all the introductory SEM texts, this one is the most interesting to read. Anyone who has taken a course in basic algebra or introductory statistics will be able to understand the ideas and work through the exercises, and those who work their way through the book will have a good foundation in SEM and will be able to use it effectively." - David F. Gillespie, George Warren Brown School of Social Work, Washington University in St. Louis, USA

"I would strongly recommend this book for use as a primary text in any SEM course. It offers a clear, applied presentation of complicated SEM techniques for a wide array of audiences with various abilities. The text would be beneficial for students with a limited background in theoretical statistics, as well as those with a strong understanding of the theoretical underpinnings of SEM. I often refer to this text in my everyday work, due to the clarity with which the material is presented." - Greg Welch, Nebraska Center for Research on Children, Youth, Families, and Schools, University of Nebraska-Lincoln, USA

Part
1. Concepts and Tools.
1. Introduction. The Book's Website.
Pedagogical Approach. Getting Ready to Learn about SEM. Characteristics of
SEM. Widespread Enthusiasm, but with a Cautionary Tale. Family History and a
Reminder about Context. Extended Latent Variable Families. Plan of the Book.
Summary.
2. Fundamental Concepts. Multiple Regression. Partial Correlation
and Part Correlation. Other Bivariate Correlations. Logistic Regression.
Statistical Tests. TOPIC BOX 2.1. The "Big Five" Misinterpretations of
Statistical Significance. Bootstrapping. Summary. Recommended Readings.
Exercises.
3. Data Preparation. Forms of Input Data. Positive Definiteness.
TOPIC BOX 3.1. Causes of Nonpositive Definiteness and Solutions. Data
Screening. Selecting Good Measures and Reporting about Them. Summary.
Recommended Readings. Exercises.
4. Computer Tools. Ease of Use, Not
Suspension of Judgment. Human-Computer Interaction. TOPIC BOX 4.1. Graphical
Isn't Always Better. Core SEM Programs and Book Website Resources. Other
Computer Tools. Summary. Recommended Readings. Part
2. Core Techniques.
5.
Specification. Steps of SEM. Model Diagram Symbols. Specification Concepts.
Path Analysis Models. CFA Models. Structural Regression Models. Exploratory
SEM. Summary. Recommended Readings. Exercises.
6. Identification. General
Requirements. Unique Estimates. Rule for Recursive Structural Models. Rules
for Nonrecursive Structural Models. Rules for Standard CFA Models. Rules for
Nonstandard CFA Models. Rules for SR Models. A Healthy Perspective on
Identification. Empirical Underidentification. Managing Identification
Problems. Summary. Recommended Readings. Exercises. APPENDIX 6.A. Evaluation
of the Rank Condition.
7. Estimation. Maximum Likelihood Estimation. TOPIC
BOX 7.1. Two-Stage Least Squares Estimation. Detailed Example. Brief Example
with a Start Value Problem. Fitting Models to Correlation Matrices.
Alternative Estimators. A Healthy Perspective on Estimation. Summary.
Recommended Readings. Exercises. APPENDIX 7.A. Start Value Suggestions for
Structural Models. APPENDIX 7.B. Effect Decomposition in Nonrecursive Models
and the Equilibrium Assumption.
8. Hypothesis Testing. Eyes on the Prize.
State of Practice, State of Mind. A Healthy Perspective on Fit Statistics.
Types of Fit Statistics and "Golden Rules." Model Chi-Square. Approximate Fit
Indexes. Visual Summaries of Fit. Recommended Approach to Model Fit
Evaluation. Detailed Example. Testing Hierarchical Models. Comparing
Nonhierarchical Models. Power Analysis. Equivalent and Near-Equivalent
Models. Summary. Recommended Readings. Exercises.
9. Measurement Models and
Confirmatory Factor Analysis. Naming and Reification Fallacies. Estimation of
CFA Models. Detailed Example. Respecification of Measurement Models. Special
Topics and Tests. TOPIC BOX 9.1. Reliability of Construct Measurement. Items
as Indicators and Other Methods for Analyzing Items. Estimated Factor Scores.
Equivalent CFA Models. Hierarchical CFA Models. Models for
MultitraitMultimethod Data. Measurement Invariance and Multiple-Sample CFA.
Summary. Recommended Readings. Exercises. APPENDIX 9.A. Start Value
Suggestions for Measurement Models. APPENDIX 9.B. Constraint Interaction in
Measurement Models.
10. Structural Regression Models. Analyzing SR Models.
Estimation of SR Models. Detailed Example. Equivalent SR Models. Single
Indicators in Partially Latent SR Models. Cause Indicators and Formative
Measurement. TOPIC BOX 10.1. Partial Least Squares Path Modeling. Invariance
Testing of SR Models. Reporting Results of SEM Analyses. Summary. Recommended
Readings. Exercises. APPENDIX 10.A. Constraint Interaction in SR Models. Part
3. Advanced Techniques, Avoiding Mistakes.
11. Mean Structures and Latent
Growth Models. Logic of Mean Structures. Identification of Mean Structures.
Estimation of Mean Structures. Latent Growth Models. Structured Means in
Measurement Models. MIMIC Models as an Alternative to Multiple-Sample
Analysis. Summary. Recommended Readings.
12. Interaction Effects and
Multilevel SEM. Interaction Effects of Observed Variables. Interaction
Effects in Path Models. Mediation and Moderation Together. Interactive
Effects of Latent Variables. Estimation with the Kenny-Judd Method.
Alternative Estimation Methods. Rationale of Multilevel Analysis. Basic
Multilevel Techniques. Convergence of SEM and MLM. Multilevel SEM. Summary.
Recommended Readings.
13. How to Fool Yourself with SEM. Tripping at the
Starting Line: Specification. Improper Care and Feeding: Data. Checking
Critical Judgment at the Door: Analysis and Respecification. The Garden Path:
Interpretation. Summary. Recommended Readings. Suggested Answers to Exercises.
Rex B. Kline, Department of Psychology, Concordia University, Montreal, Quebec, Canada