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Principles and Practice of Structural Equation Modeling: Second Edition 2nd edition [Hardback]

4.11/5 (196 ratings by Goodreads)
  • Formāts: Hardback, 366 pages, height x width: 229x152 mm, weight: 656 g
  • Sērija : Methodology in the Social Sciences
  • Izdošanas datums: 09-Dec-2004
  • Izdevniecība: Guilford Publications
  • ISBN-10: 1593850751
  • ISBN-13: 9781593850753
Citas grāmatas par šo tēmu:
  • Formāts: Hardback, 366 pages, height x width: 229x152 mm, weight: 656 g
  • Sērija : Methodology in the Social Sciences
  • Izdošanas datums: 09-Dec-2004
  • Izdevniecība: Guilford Publications
  • ISBN-10: 1593850751
  • ISBN-13: 9781593850753
Citas grāmatas par šo tēmu:
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.

Recenzijas

'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 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

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. He succeeds in conveying the conceptual complexity of SEM without sacrificing the reader's understanding of the ramifications of the model's assumptions. [ ...] In fact, he succinctly summarises all you need to know on multiple regression and correlation in one of the first chapters of his book. [ ...] I was agreeably surprised by Kline's introductio to the topic. Despite having read other publications on SEM ... I nonetheless discovered a lot of interesting new concepts. [ ...] This textbook covers the full gamut of the different structural models [ ...] SEMs are a relatively new group of procedures, which has initially become popular for its actual simplicity and intuitive logic. This book defintiely gifvews 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, Imperial College, London in The Psychologist, January 2006

I. FUNDAMENTAL CONCEPTS
1 Introduction
3(17)
1.1 Plan of the Book
3(3)
1.2 Notation
6(1)
1.3 Computer Programs for SEM
6(2)
1.4 Statistical Journeys
8(1)
1.5 Family Values
9(7)
1.6 Extended Latent Variable Families
16(1)
1.7 Family History
17(1)
1.8 Internet Resources
18(1)
1.9 Summary
19(1)
2 Basic Statistical Concepts: I. Correlation and Regression
20(25)
2.1 Standardized and Unstandardized Variables
20(2)
2.2 Bivariate Correlation and Regression
22(7)
2.3 Partial Correlation
29(1)
2.4 Multiple Correlation and Regression
30(10)
2.5 Statistical Tests
40(2)
2.6 Bootstrapping
42(1)
2.7 Summary
43(1)
2.8 Recommended Readings
44(1)
3 Basic Statistical Concepts: II. Data Preparation and Screening
45(18)
3.1 Data Preparation
45(3)
3.2 Data Screening
48(10)
3.3 Score Reliability and Validity
58(3)
3.4 Summary
61(1)
3.5 Recommended Readings
62(1)
4 Core SEM Techniques and Software
63(30)
4.1 Steps of SEM
63(3)
4.2 Path Analysis: A Structural Model of Illness Factors
66(4)
4.3 Confirmatory Factor Analysis: A Measurement Model of Arousal
70(4)
4.4 A Structural Regression Model of Family Risk and Child Adjustment
74(3)
4.5 Extensions
77(1)
4.6 SEM Computer Programs
77(12)
4.7 Summary
89(1)
4.8 Recommended Readings
90(3)
II. CORE TECHNIQUES
5 Introduction to Path Analysis
93(30)
5.1 Correlation and Causation
93(2)
5.2 Specification of Path Models
95(7)
5.3 Types of Path Models
102(3)
5.4 Principles of Identification
105(5)
5.5 Sample Size
110(1)
5.6 Overview of Estimation Options
111(1)
5.7 Maximum Likelihood Estimation
112(5)
5.8 Other Issues
117(3)
5.9 Summary
120(1)
5.10 Recommended Readings
120(1)
APPENDIX 5.A Recommendations for Start Values
121(1)
APPENDIX 5.B Effect Size Interpretation of Standardized Path Coefficients
121(2)
6. Details of Path Analysis
123(42)
6.1 Detailed Analysis of a Recursive Model of Illness Factors
123(10)
6.2 Assessing Model Fit
133(12)
6.3 Testing Hierarchical Models
145(8)
6.4 Comparing Nonhierarchical Models 151
6.5 Equivalent Models
153(3)
6.6 Power Analysis
156(2)
6.7 Other Estimation Options
158(2)
6.8 Summary
160(1)
6.9 Recommended Readings
161(1)
APPENDIX 6.A Statistical Tests for Indirect Effects in Recursive Path Models
162(1)
APPENDIX 6.B Amos Basic Syntax
163(1)
APPENDIX 6.C Estimation of Recursive Path Models with Multiple Regression
164(1)
7. Measurement Models and Confirmatory Factor Analysis
165(44)
7.1 Specification of CFA Models
165(4)
7.2 Identification of CFA Models
169(6)
7.3 Naming and Reification Fallacies
175(1)
7.4 Estimation of CFA Models
176(4)
7.5 Testing CFA Models
180(12)
7.6 Equivalent CFA Models
192(2)
7.7 Analyzing Indicators with Nonnormal Distributions
194(4)
7.8 Special Types of CFA Models
198(6)
7.9 Other Issues
204(2)
7.10 Summary
206(1)
7.11 Recommended Readings
206(1)
APPENDIX 7.A Recommendations for Start Values
207(1)
APPENDIX 7.B CALIS Syntax
207(2)
8 Models with Structural and Measurement Components
209(28)
8.1 Characteristics of SR Models
209(2)
8.2 Analysis of Hybrid Models
211(8)
8.3 Estimation of SR Models
219(2)
8.4 A Detailed Example
221(8)
8.5 Other Issues
229(3)
8.6 Summary
232(1)
8.7 Recommended Readings
233(1)
APPENDIX 8.A SEPATH Syntax
234(3)
III. ADVANCED TECHNIQUES; AVOIDING MISTAKES
9 Nonrecursive Structural Models
237(26)
9.1 Specification of Nonrecursive Models
237(3)
9.2 Identification of Nonrecursive Models
240(9)
9.3 Estimation of Nonrecursive Models
249(5)
9.4 Examples
254(6)
9.5 Summary
260(1)
9.6 Recommended Readings
261(1)
APPENDIX 9.A EQS Syntax
262(1)
10 Mean Structures and Latent Growth Models
263(26)
10.1 Introduction to Mean Structures
263(4)
10.2 Identification of Mean Structures
267(1)
10.3 Estimation of Mean Structures
268(1)
10.4 Structured Means in Measurement Models
269(3)
10.5 Latent Growth Models
272(13)
10.6 Extensions
285(2)
10.7 Summary
287(1)
10.8 Recommended Readings
287(1)
APPENDIX 10.A Mplus Syntax
288(1)
11 Multiple-Sample SEM
289(24)
11.1 Rationale of Multiple-Sample SEM
289(1)
11.2 Multiple-Sample Path Analysis
290(5)
11.3 Multiple-Sample CFA
295(11)
11.4 Extensions
306(1)
11.5 MIMIC Models as an Alternative to Multiple-Sample Analysis
307(3)
11.6 Summary
310(1)
11.7 Recommended Readings
311(1)
APPENDIX 11.A LISREL SIMPLIS Syntax
312(1)
12 How to Fool Yourself with SEM
313(12)
12.1 Tripping at the Starting Line: Specification
313(3)
12.2 Improper Care and Feeding: Data
316(2)
12.3 Checking Critical Judgment at the Door: Analysis and Respecification
318(3)
12.4 The Garden Path: Interpretation
321(3)
12.5 Summary
324(1)
12.6 Recommended Readings
324(1)
13 Other Horizons
325(13)
13.1 Interaction and Curvilinear Effects
325(7)
13.2 Multilevel Structural Equation Models
332(4)
13.3 Summary
336(1)
13.4 Recommended Readings
337(1)
References 338(14)
Author Index 352(4)
Subject Index 356


Rex B. Kline, PhD, is an associate professor of Psychology at Concordia University in Montreal, Canada