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Principles and Practice of Structural Equation Modeling, Second Edition...
by Kline, Rex B. | PB | Good
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eBay item number:373460535693
Item specifics
- Condition
- Good
- Seller Notes
- Binding
- Paperback
- Weight
- 0 lbs
- Product Group
- Book
- IsTextBook
- Yes
- ISBN
- 9781572306905
- Publication Name
- Principles and Practice of Structural Equation Modeling, Second Edition
- Item Length
- 9in
- Publisher
- Guilford Publications
- Publication Year
- 2004
- Series
- Methodology in the Social Sciences Ser.
- Type
- Textbook
- Format
- Trade Paperback
- Language
- English
- Item Height
- 1in
- Features
- Revised
- Item Width
- 6.3in
- Item Weight
- 24.1 Oz
- Number of Pages
- 366 Pages
About this product
Product Information
This popular text provides an accessible guide to the application, interpretation, and pitfalls of structural equation modeling (SEM). Reviewed are fundamental statistical concepts--such as correlation, regressions, data preparation and screening, path analysis, and confirmatory factor analysis--as well as more advanced methods, including the evaluation of nonlinear effects, measurement models and structural regression models, latent growth models, and multilevel SEM. The companion Web page offers data and program syntax files for many of the research examples, electronic overheads that can be downloaded and printed by instructors or students, and links to SEM-related resources.
Product Identifiers
Publisher
Guilford Publications
ISBN-10
1572306904
ISBN-13
9781572306905
eBay Product ID (ePID)
30795301
Product Key Features
Publication Name
Principles and Practice of Structural Equation Modeling, Second Edition
Format
Trade Paperback
Language
English
Features
Revised
Publication Year
2004
Series
Methodology in the Social Sciences Ser.
Type
Textbook
Number of Pages
366 Pages
Dimensions
Item Length
9in
Item Height
1in
Item Width
6.3in
Item Weight
24.1 Oz
Additional Product Features
Lc Classification Number
Qa278.K585 2005
Edition Description
Revised Edition
Edition Number
2
Reviews
'SEM can be relatively difficult to learn for researchers without a strong grounding in matrix algebra. Kline, however, hits the nail on the head. He perfectly addresses the needs of social psychologists without formal training in mathematical statistics... This book defintiely gives justice to this aspect of SEM. It can be read by any graduate in psychology or even by keen undergraduates interested in exploring new vistas. Yet it will also constitute a surprisingly good read for experienced researchers in search of some refreshing insights in their favourite techniques. Kline has indeed negotiated a real tour de force with this second edition by succeeding in reconciling comprehensiveness and comprehensibility.' - Cedric Gineset, The Psychologist, A good book has gotten much better. Since the first edition appeared in 1998, Kline's book has been the only one I assign in my SEM course. It easily surpassed its competitors in clarity and accessibility, without sacrificing accuracy and completeness. This new edition is a major upgrade, with substantial reworking of the original chapters to add depth and clarity, as well as new chapters on topics like latent growth curve modeling and hierarchical linear modeling./m-/Paul D. Allison, Department of Sociology, University of Pennsylvania "An outstanding introduction to SEM, geared toward the beginner in this area. The relaxed, conversational writing style makes access to this complex material pain-free and easy. The book strikes a perfect balance between easy reading and the presentation of technical detail and technical terms. I recommend this book strongly, and I will use it the next time I teach SEM."-Alexander von Eye, Department of Psychology, Michigan State University "An excellent choice....The book strikes a nice balance between the technical and practical aspects of SEM. A particular strength is that the examples include correlations and standard deviations, so that readers can execute the examples using various SEM software."-Fred E. Markowitz, Department of Sociology, Northern Illinois University "An extremely important resource for both the theoretical and applied researcher interested in SEM. Dr. Kline's work contains information that is insightful, accurate, and practical. I recommend this book as both a text for graduate-level seminars and a technical resource for research."-Larry Price, College of Education, Texas State University-San Marcos "The approach to SEM is wonderful. Difficult concepts and issues are explained in a way that is accessible to those who are not trained as quantitative methodologists. The blend of conceptual and procedural explanations is generally very good, and the discussions and explanations are technically accurate."-Xitao Fan, Curry School of Education, University of Virginia, "Perfectly addresses the needs of social scientists like me without formal training in mathematical statistics....Succeeds in conveying the conceptual complexity of SEM without sacrificing the reader's understanding of the ramifications of the model's assumptions....Can be read by any graduate in psychology or even by keen undergraduates interested in exploring new vistas. Yet it will also constitute a surprisingly good read for experienced researchers in search of some refreshing insights in their favorite techniques....A real tour de force....Succeeds in reconciling comprehensiveness and comprehensibility."--The Psychologist "Structural equation modeling is an important tool in research in the social sciences, and this updated edition keeps pace with the newest methodologies, including providing a SEM-text web page with free access to data and program files for the examples here."--SciTech Book News "...the greatest strength of this book is Kline's ability to present materials in an engaging, accessible manner. In nearly all situations, Kline is able to describe even the more complex material in practical, (relatively) jargon-free terms....In this regard, this book is unparalleled, and I suspect that this strength alone will make this the book of choice for many who are eager to learn SEM but who do not possess extensive quantitative backgrounds....it provides better treatment of some of the more advanced topics....This book represents a well-written introduction to SEM that will be accessible to readers with minimal quantitative background....This book could be readily adapted to courses for students with a basic understanding of correlation and regression or as part of a course for more advanced students."--APAPsycCRITIQUES "...Perfectly addresses the need of social scientists like me without formal training in mathematical statistics....the book is rich in examples from different fields....It can be read by any graduate [student] in psychology or even by keen undergraduates interested in exploring new vistas....it will also constitute a surprisingly good read for experienced researchers in search of some refreshing insights in their favourite techniques....a real tour de force."--The Psychologist "This wonderfully written book is an impressive introduction to structural equation models (SEM) containing a sharp mix of expert analysis and observations....Contains important resources for both theoretical and applied researchers interested in SEMs...appropriate as a text for graduate students and a reference for researchers, providing both audiences with valuable insight into the subject matter...A well-written book that will be useful for graduate students and researchers."--Journal of the American Statistical Association, "Structural equation modeling is an important tool in research in the social sciences, and this updated edition keeps pace with the newest methodologies, including providing a SEM-text web page with free access to data and program files for the examples here."--SciTech Book News "...the greatest strength of this book is Kline's ability to present materials in an engaging, accessible manner. In nearly all situations, Kline is able to describe even the more complex material in practical, (relatively) jargon-free terms....In this regard, this book is unparalleled, and I suspect that this strength alone will make this the book of choice for many who are eager to learn SEM but who do not possess extensive quantitative backgrounds....it provides better treatment of some of the more advanced topics....This book represents a well-written introduction to SEM that will be accessible to readers with minimal quantitative background....This book could be readily adapted to courses for students with a basic understanding of correlation and regression or as part of a course for more advanced students."--PsycCRITIQUES, "Perfectly addresses the needs of social scientists like me without formal training in mathematical statistics....Succeeds in conveying the conceptual complexity of SEM without sacrificing the reader's understanding of the ramifications of the model's assumptions....Can be read by any graduate in psychology or even by keen undergraduates interested in exploring new vistas. Yet it will also constitute a surprisingly good read for experienced researchers in search of some refreshing insights in their favorite techniques....A real tour de force....Succeeds in reconciling comprehensiveness and comprehensibility."--The Psychologist "Structural equation modeling is an important tool in research in the social sciences, and this updated edition keeps pace with the newest methodologies, including providing a SEM-text web page with free access to data and program files for the examples here."--SciTech Book News "...the greatest strength of this book is Kline's ability to present materials in an engaging, accessible manner. In nearly all situations, Kline is able to describe even the more complex material in practical, (relatively) jargon-free terms....In this regard, this book is unparalleled, and I suspect that this strength alone will make this the book of choice for many who are eager to learn SEM but who do not possess extensive quantitative backgrounds....it provides better treatment of some of the more advanced topics....This book represents a well-written introduction to SEM that will be accessible to readers with minimal quantitative background....This book could be readily adapted to courses for students with a basic understanding of correlation and regression or as part of a course for more advanced students."--PsycCRITIQUES "...Perfectly addresses the need of social scientists like me without formal training in mathematical statistics....the book is rich in examples from different fields....It can be read by any graduate [student] in psychology or even by keen undergraduates interested in exploring new vistas....it will also constitute a surprisingly good read for experienced researchers in search of some refreshing insights in their favourite techniques....a real tour de force."--The Psychologist
Table of Content
Contents I. Fundamental Concepts 1. Introduction 1.1. Plan of the Book 1.2. Notation 1.3. Computer Programs for SEM 1.4. Statistical Journeys 1.5. Family Values 1.6. Extend Latent Variable Families 1.7. Family History 1.8. Internet Resources 1.9. Summary 2. Basic Statistical Concepts: I. Correlation and Regression 2.1. Standardized and Unstandardized Variables 2.2. Bivariate Correlation and Regression 2.3. Partial Correlation 2.4. Multiple Correlation and Regression 2.5. Statistical Tests 2.6. Bootstrapping 2.7. Summary 2.8. Recommended Readings 3. Basic Statistical Concepts: II. Data Preparation and Screening 3.1. Data Preparation 3.2. Data Screening 3.3. Score Reliability and Validity 3.4. Summary 3.5. Recommended Readings 4. Core SEM Techniques and Software 4.1. Steps of SEM 4.2. Path Analysis: A Structural Model of Illness Factors 4.3. Confirmatory Factor Analysis: A Measurement Model of Arousal 4.4. A Structural Regression Model of Family Risk and Child Adjustment 4.5. Extensions 4.6. SEM Computer Programs 4.7. Summary 4.8. Recommended Readings II. Core SEM Techniques 5. Introduction to Path Analysis 5.1. Correlation and Causation 5.2. Specification of Path Models 5.3. Types of Path Models 5.4. Principles of Identification 5.5. Sample Size 5.6. Overview of Estimation Options 5.7. Maximum Likelihood Estimation 5.8. Other Issues 5.9. Summary 5.10. Recommended Readings Appendix 5.a. Recommendations for Start Values Appendix 5.b. Effect Size Interpretation of Standardized Path Coefficients 6. Details of Path Analysis 6.1. Detailed Analysis of a Recursive Model of Illness Factors 6.2. Assessing Model Fit 6.3. Testing Hierarchical Models 6.4. Comparing Nonhierarchical Models 6.5. Equivalent Models 6.6. Power Analysis 6.7. Other Estimation Options 6.8. Summary 6.9. Recommended Readings Appendix 6.a. Statistical Tests for Indirect Effects in Recursive Path Models Appendix 6.b. Amos Basic Syntax Appendix 6.c. Estimation of Recursive Path Models with Multiple Regression 7. Measurement Models and Confirmatory Factor Analysis 7.1. Specification of CFA Models 7.2. Identification of CFA Models 7.3. Naming and Reification Fallacies 7.4. Estimation of CFA Models 7.5. Testing CFA Models 7.6. Equivalent CFA Models 7.7. Analyzing Indicators with Non-Normal Distributions 7.8. Special Types of CFA Models 7.9. Other Issues 7.10. Summary 7.11. Recommended Readings Appendix 7.a. Recommendations for Start Values Appendix 7.b. CALIS Syntax 8. Models with Structural and Measurement Components 8.1. Characteristics of SR Models 8.2. Analysis of SR Models 8.3. Estimation of SR Models 8.4. A Detailed Example 8.5. Other Issues 8.6. Summary 8.7. Recommended Readings Appendix 8.a. SEPATH Syntax III. Advanced Techniques, Avoiding Mistakes 9. Nonrecursive Structural Models 9.1. Specification of Nonrecursive Models 9.2. Identification of Nonrecursive Models 9.3. Estimation of Nonrecursive Models 9.4. Examples 9.5. Summary 9.6. Recommended Readings Appendix 9.a. EQS Syntax 10. Mean Structures and Latent Growth Models 10.1. Introduction to Mean Structures 10.2. Identification of Mean Structures 10.3. Estimation of Mean Structures 10.4. Structured Means in Measurement Models 10.5. Latent Growth Models 10.6. Extensions 10.7. Summary 10.8. Recommended Readings Appendix 10.a. Mplus Syntax 11. Multiple-Sample SEM 11.1. Rationale of Multiple-Sample SEM 11.2. Multiple-Sample Path Analysis 11.3. Multiple-Sample CFA 11.4. Extensions 11.5. MIMIC Models as an Alternative to Multiple-Sample Analysis 11.6. Summary 11.7. Recommended Readings Appendix 11.a. LISREL SIMPLIS Syntax 12. How to Fool Yourself with SEM 12.1. Tripping at t
Copyright Date
2005
Target Audience
Scholarly & Professional
Topic
Methodology, Probability & Statistics / Multivariate Analysis, Management, Statistics, Research & Methodology
Lccn
2004-019784
Dewey Decimal
519.5/35
Dewey Edition
21
Genre
Psychology, Business & Economics, Mathematics, Social Science
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