Atnaujinkite slapukų nuostatas

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

4.11/5 (258 ratings by Goodreads)
  • Formatas: Paperback / softback, 422 pages, aukštis x plotis: 246x174 mm, weight: 774 g
  • Serija: Methodology in the Social Sciences
  • Išleidimo metai: 07-Sep-2010
  • Leidėjas: Guilford Publications
  • ISBN-10: 1606238760
  • ISBN-13: 9781606238769
Kitos knygos pagal šią temą:
  • Formatas: Paperback / softback, 422 pages, aukštis x plotis: 246x174 mm, weight: 774 g
  • Serija: Methodology in the Social Sciences
  • Išleidimo metai: 07-Sep-2010
  • Leidėjas: Guilford Publications
  • ISBN-10: 1606238760
  • ISBN-13: 9781606238769
Kitos knygos pagal šią temą:
"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. The reorganization of the material, new topic boxes, new Web page, and updated technical information enhance an already great resource."---James B. Schreiber, Center for Advancing the Study of Teaching and Learning, Duquesne University

"In the third edition, Kline not only has updated the material, but has substantially improved it. He adds more depth to certain topics---such as estimation, in Chapter 7---and covers some intermediate-to-advanced topics not described in the previous edition, all at a level appropriate for beginners."---Noel A. Card, Division of Family Studies and Human Development, University of Arizona

"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

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.



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 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.

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 I CONCEPTS AND TOOLS
1 Introduction
3(16)
The Book's Website
3(1)
Pedagogical Approach
4(1)
Getting Ready to Learn about SEM
5(2)
Characteristics of SEM
7(6)
Widespread Enthusiasm, but with a Cautionary Tale
13(2)
Family History and a Reminder about Context
15(1)
Extended Latent Variable Families
16(1)
Plan of the Book
17(1)
Summary
18(1)
2 Fundamental Concepts
19(27)
Multiple Regression
19(9)
Partial Correlation and Part Correlation
28(3)
Other Bivariate Correlations
31(1)
Logistic Regression
32(1)
Statistical Tests
33(9)
Bootstrapping
42(1)
Summary
43(1)
Recommended Readings
44(1)
Exercises
45(1)
3 Data Preparation
46(29)
Forms of Input Data
46(3)
Positive Definiteness
49(2)
Data Screening
51(17)
Selecting Good Measures and Reporting about Them
68(4)
Summary
72(1)
Recommended Readings
72(1)
Exercises
73(2)
4 Computer Tools
75(16)
Ease of Use, Not Suspension of Judgment
75(2)
Human-Computer Interaction
77(1)
Core SEM Programs and Book Website Resources
77(9)
Other Computer Tools
86(1)
Summary
87(1)
Recommended Readings
87(4)
PART II CORE TECHNIQUES
5 Specification
91(33)
Steps of SEM
91(4)
Model Diagram Symbols
95(1)
Specification Concepts
96(7)
Path Analysis Models
103(9)
CFA Models
112(6)
Structural Regression Models
118(3)
Exploratory SEM
121(1)
Summary
121(1)
Recommended Readings
122(1)
Exercises
122(2)
6 Identification
124(30)
General Requirements
124(6)
Unique Estimates
130(2)
Rule for Recursive Structural Models
132(1)
Rules for Nonrecursive Structural Models
132(5)
Rules for Standard CFA Models
137(1)
Rules for Nonstandard CFA Models
138(6)
Rules for SR Models
144(2)
A Healthy Perspective on Identification
146(1)
Empirical Underidentification
146(1)
Managing Identification Problems
147(1)
Summary
148(1)
Recommended Readings
149(1)
Exercises
149(2)
Appendix 6.A Evaluation of the Rank Condition
151(3)
7 Estimation
154(35)
Maximum Likelihood Estimation
154(6)
Detailed Example
160(12)
Brief Example with a Start Value Problem
172(3)
Fitting Models to Correlation Matrices
175(1)
Alternative Estimators
176(6)
A Healthy Perspective on Estimation
182(1)
Summary
182(1)
Recommended Readings
183(1)
Exercises
183(2)
Appendix 7.A Start Value Suggestions for Structural Models
185(1)
Appendix 7.B Effect Decomposition in Nonrecursive Models and the Equilibrium Assumption
186(1)
Appendix 7.C Corrected Proportions of Explained Variance for Nonrecursive Models
187(2)
8 Hypothesis Testing
189(41)
Eyes on the Prize
189(1)
State of Practice, State of Mind
190(1)
A Healthy Perspective on Fit Statistics
191(2)
Types of Fit Statistics and "Golden Rules"
193(6)
Model Chi-Square
199(5)
Approximate Fit Indexes
204(5)
Visual Summaries of Fit
209(1)
Recommended Approach to Model Fit Evaluation
209(1)
Detailed Example
210(4)
Testing Hierarchical Models
214(5)
Comparing Nonhierarchical Models
219(3)
Power Analysis
222(3)
Equivalent and Near-Equivalent Models
225(3)
Summary
228(1)
Recommended Readings
228(1)
Exercises
229(1)
9 Measurement Models and Confirmatory Factor Analysis
230(35)
Naming and Reification Fallacies
230(1)
Estimation of CFA Models
231(2)
Detailed Example
233(7)
Respecification of Measurement Models
240(1)
Special Topics and Tests
241(3)
Items as Indicators and Other Methods for Analyzing Items
244(1)
Estimated Factor Scores
245(1)
Equivalent CFA Models
245(3)
Hierarchical CFA Models
248(2)
Models for Multitrait-Multimethod Data
250(1)
Measurement Invariance and Multiple-Sample CFA
251(10)
Summary
261(1)
Recommended Readings
262(1)
Exercises
262(1)
Appendix 9.A Start Value Suggestions for Measurement Models
263(1)
Appendix 9.B Constraint Interaction in Measurement Models
264(1)
10 Structural Regression Models
265(34)
Analyzing SR Models
265(4)
Estimation of SR Models
269(1)
Detailed Example
270(6)
Equivalent SR Models
276(1)
Single Indicators in Partially Latent SR Models
276(4)
Cause Indicators and Formative Measurement
280(8)
Invariance Testing of SR Models
288(1)
Reporting Results of SEM Analyses
289(4)
Summary
293(1)
Recommended Readings
293(1)
Exercises
294(1)
Appendix 10.A Constraint Interaction in SR Models
295(4)
PART III ADVANCED TECHNIQUES, AVOIDING MISTAKES
11 Mean Structures and Latent Growth Models
299(28)
Logic of Mean Structures
299(4)
Identification of Mean Structures
303(1)
Estimation of Mean Structures
304(1)
Latent Growth Models
304(12)
Structured Means in Measurement Models
316(6)
MIMIC Models as an Alternative to Multiple-Sample Analysis
322(3)
Summary
325(1)
Recommended Readings
326(1)
12 Interaction Effects and Multilevel SEM
327(29)
Interaction Effects of Observed Variables
327(4)
Interaction Effects in Path Models
331(2)
Mediation and Moderation Together
333(3)
Interactive Effects of Latent Variables
336(1)
Estimation with the Kenny-Judd Method
337(3)
Alternative Estimation Methods
340(3)
Rationale of Multilevel Analysis
343(2)
Basic Multilevel Techniques
345(3)
Convergence of SEM and MLM
348(2)
Multilevel SEM
350(4)
Summary
354(1)
Recommended Readings
354(2)
13 How to Fool Yourself with SEM
356(11)
Tripping at the Starting Line: Specification
356(3)
Improper Care and Feeding: Data
359(2)
Checking Critical Judgment at the Door: Analysis and Respecification
361(2)
The Garden Path: Interpretation
363(3)
Summary
366(1)
Recommended Readings
366(1)
Suggested Answers to Exercises 367(20)
References 387(18)
Author Index 405(6)
Subject Index 411(16)
About the Author 427
Rex B. Kline, PhD, is Professor of Psychology at Concordia University in Montreal, Quebec, Canada. Since earning a doctorate in clinical psychology, he has conducted research on the psychometric evaluation of cognitive abilities, child clinical assessment, structural equation modeling, training of behavioral science researchers, and usability engineering in computer science. Dr. Kline has published five books, six chapters, and more than 40 articles in research journals.