Principles and practice of structural equation modeling:
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
New York ; London
The Guilford Press
[2016]
|
| Edition: | Fourth edition |
| Series: | Methodology in the social sciences
|
| Subjects: | |
| Online Access: | TUM01 UBA01 UBG01 UBW01 UER01 UPA01 Inhaltsverzeichnis |
| Physical Description: | 1 Online-Ressource (xvii, 534 Seiten) Iillustrationen |
| ISBN: | 9781462523368 |
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| 245 | 1 | 0 | |a Principles and practice of structural equation modeling |c Rex B. Kline ; series editor's note by Todd D. Little |
| 250 | |a Fourth edition | ||
| 264 | 1 | |a New York ; London |b The Guilford Press |c [2016] | |
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| 650 | 7 | |a Structural equation modeling |2 fast | |
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Record in the Search Index
| _version_ | 1804177027666804736 |
|---|---|
| adam_text | Titel: Principles and practice of structural equation modeling
Autor: Kline, Rex B
Jahr: 2016
Contents
Introduction
Book Website 2
Pedagogical Approach 2
Principles over Computer Tools 3
Symbols and Notation 3
Life s a Journey, Not a Destination 3
Plan of the Book 4
PART I. CONCEPTS AND TOOLS
1 • Coming of Age
Preparing to Learn SEM 7
Definition of SEM 9
Importance of Theory 10
A Priori, but Not Exclusively Confirmatory 11
Probabilistic Causation 11
Observed Variables and Latent Variables 12
Data Analyzed in SEM 13
SEM Requires Large Samples 14
Less Emphasis on Significance Testing 17
SEM and Other Statistical Techniques 17
SEM and Other Causal Inference Frameworks 18
Myths about SEM 20
Widespread Enthusiasm, but with a Cautionary Tale
Family History 23
Summary 24
Learn More 24
xii Contents
2 • Regression Fundamentals 25
Bivariate Regression 25
Multiple Regression 30
Left-Out Variables Error 35
Suppression 36
Predictor Selection and Entry 37
Partial and Part Correlation 39
Observed versus Estimated Correlations 41
Logistic Regression and Probit Regression 44
Summary 47
Learn More 47
Exercises 48
3 • Significance Testing and Bootstrapping 49
Standard Errors 49
Critical Ratios 51
Power and Types of Null Hypotheses 52
Significance Testing Controversy 54
Confidence Intervals and Noncentral Test Distributions 57
Bootstrapping 60
Summary 62
Learn More 62
Exercises 63
4 • Data Preparation and Psychometrics Review 64
Forms of Input Data 64
Positive Definiteness 67
Extreme Collinearity 71
Outliers 72
Normality 74
Transformations 77
Relative Variances 81
Missing Data 82
Selecting Good Measures and Reporting about Them 88
Score Reliability 90
Score Validity 93
Item Response Theory and Item Characteristic Curves 94
Summary 95
Learn More 96
Exercises 96
5 • Computer Tools 97
Ease of Use, Not Suspension of Judgment 97
Human—Computer Interaction 98
Tips for SEM Programming 100
SEM Computer Tools 101
Other Computer Resources for SEM 111
Computer Tools for the SCM 112
Summary 113
Learn More 113
PART II. SPECIFICATION AND IDENTIFICATION
6 • Specification of Observed Variable (Path) Models
Steps of SEM 117
Model Diagram Symbols 121
Causal Inference 122
Specification Concepts 126
Path Analysis Models 129
Recursive and Nonrecursive Models 133
Path Models for Longitudinal Data 138
Summary 141
Learn More 142
Exercises 142
APPENDIX 6.A. LISREL Notation for Path Models
7 • Identification of Observed-Variable (Path) Models
General Requirements 145
Unique Estimates 148
Rule for Recursive Models 149
Identification of Nonrecursive Models 150
Models with Feedback Loops and All Possible
Disturbance Correlations 150
Graphical Rules for Other Types of Nonrecursive Models 153
Respecification of Nonrecursive Models That Are Not Identified 155
A Healthy Perspective on Identification 157
Empirical Underidentification 157
Managing Identification Problems 158
Path Analysis Research Example 159
Summary 159
Learn More 160
Exercises 160
APPENDIX 7.A. Evaluation of the Rank Condition
8 • Graph Theory and the Structural Causal Model
Introduction to Graph Theory 164
Elementary Directed Graphs and Conditional Independences 166
xiv Contents
Implications for Regression Analysis 170
d-Separation 170
Basis Set 173
Causal Directed Graphs 174
Testable Implications 176
Graphical Identification Criteria 177
Instrumental Variables 180
Causal Mediation 181
Summary 184
Leam More 185
Exercises 185
APPENDIX 8.A. Locating Conditional Independences in Directed Cyclic Graphs 1 86
APPENDIX 8.B. Counterfactual Definitions of Direct and Indirect Effects 1 87
9 • Specification and Identification 1 88
of Confirmatory Factor Analysis Models
Latent Variables in CFA 188
Factor Analysis 189
Characteristics of EFA Models 191
Characteristics of CFA Models 193
Other CFA Specification Issues 195
Identification of CFA Models 198
Rules for Standard CFA Models 201
Rules for Nonstandard CFA Models 202
Empirical Underidentification in CFA 206
CFA Research Example 206
Summary 207
Learn More 207
Exercises 209
APPENDIX 9.A. LISREL Notation for CFA Models 210
10* Specification and Identification 212
of Structural Regression Models
Causal Inference with Latent Variables 212
Types of SR Models 213
Single Indicators 214
Identification of SR Models 217
Exploratory SEM 219
SR Model Research Examples 220
Summary 223
Learn More 225
Exercises 225
APPENDIX 10.A. LISREL Notation for SR Models
226
PART III. ANALYSIS
11* Estimation and Local Fit Testing
Types of Estimators 231
Causal Effects in Path Analysis 232
Single-Equation Methods 233
Simultaneous Methods 235
Maximum Likelihood Estimation 235
Detailed Example 239
Fitting Models to Correlation Matrices 253
Alternative Estimators 255
A Healthy Perspective on Estimation 258
Summary 259
Learn More 259
Exercises 260
APPENDIX I I.A. Start Value Suggestions for Structural Models
12* Global Fit Testing
State of Practice, State of Mind 262
A Healthy Perspective on Global Fit Statistics 263
Model Test Statistics 265
Approximate Fit Indexes 266
Recommended Approach to Fit Evaluation 268
Model Chi-Square 270
RMSEA 273
SRMR 277
Tips for Inspecting Residuals 278
Global Fit Statistics for the Detailed Example 278
Testing Hierarchical Models 280
Comparing Nonhierarchical Models 286
Power Analysis 290
Equivalent and Near-Equivalent Models 292
Summary 297
Learn More 298
Exercises 298
APPENDIX 12.A. Model Chi-Squares Printed by LISREL
13* Analysis of Confirmatory Factor Analysis Models
Fallacies about Factor or Indicator Labels 300
Estimation of CFA Models 301
Detailed Example 304
Respecification of CFA Models 309
Special Topics and Tests 312
Equivalent CFA Models 315
Special CFA Models 319
xvi Contents
Analyzing Likert-Scale Items as Indicators 323
Item Response Theory as an Alternative to CFA 332
Summary 333
Learn More 333
Exercises 334
APPENDIX 13.A. Start Value Suggestions for Measurement Models 335
APPENDIX 13.B. Constraint Interaction in CFA Models 336
14* Analysis of Structural Regression Models 338
Two-Step Modeling 338
Four-Step Modeling 339
Interpretation of Parameter Estimates and Problems 340
Detailed Example 341
Equivalent SR Models 348
Single Indicators in a Nonrecursive Model 349
Analyzing Formative Measurement Models in SEM 352
Summary 361
Learn More 362
Exercises 362
APPENDIX 14.A. Constraint Interaction in SR Models 363
APPENDIX 14.B. Effect Decomposition in Nonrecursive Models 364
and the Equilibrium Assumption
APPENDIX 14.C. Corrected Proportions of Explained Variance 365
for Nonrecursive Models
PART IV. ADVANCED TECHNIQUES AND BEST PRACTICES
15* Mean Structures and Latent Growth Models 369
Logic of Mean Structures 369
Identification of Mean Structures 373
Estimation of Mean Structures 374
Latent Growth Models 374
Detailed Example 375
Comparison with a Polynomial Growth Model 387
Extensions of Latent Growth Models 390
Summary 392
Learn More 392
Exercises 393
16 • Multiple-Samples Analysis and Measurement Invariance 394
Rationale of Multiple-Samples SEM 394
Measurement Invariance 396
Testing Strategy and Related Issues 399
Example with Continuous Indicators 403
Contents xvii
Example with Ordinal Indicators 411
Structural Invariance 420
Alternative Statistical Techniques 420
Summary 421
Learn More 421
Exercises 422
APPENDIX 16.A. Welch-James Test 423
17* Interaction Effects and Multilevel 424
Structural Equation Modeling
Interactive Effects of Observed Variables 424
Interactive Effects in Path Analysis 431
Conditional Process Modeling 432
Causal Mediation Analysis 435
Interactive Effects of Latent Variables 437
Multilevel Modeling and SEM 444
Summary 450
Learn More 450
Exercises 451
18* Best Practices in Structural Equation Modeling 452
Resources 452
Specification 454
Identification 457
Measures 458
Sample and Data 458
Estimation 461
Respecification 463
Tabulation 464
Interpretation 465
Avoid Confirmation Bias 466
Bottom Lines and Statistical Beauty 466
Summary 467
Learn More 467
Suggested Answers to Exercises 469
References 489
Author Index 510
Subject Index 516
About the Author 534
The companion website www.guilford.com/kline-materials provides
downloadable data, syntax, and output for all the book s examples in
six widely used SEM computer tools and links to related web pages.
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| indexdate | 2024-07-10T07:41:33Z |
| institution | BVB |
| isbn | 9781462523368 |
| language | English |
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| publishDate | 2016 |
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| record_format | marc |
| series2 | Methodology in the social sciences |
| spelling | Kline, Rex B. Verfasser (DE-588)1026732069 aut Principles and practice of structural equation modeling Rex B. Kline ; series editor's note by Todd D. Little Fourth edition New York ; London The Guilford Press [2016] © 2016 1 Online-Ressource (xvii, 534 Seiten) Iillustrationen txt rdacontent c rdamedia cr rdacarrier Methodology in the social sciences MATHEMATICS / Applied bisacsh MATHEMATICS / Probability & Statistics / General bisacsh Social sciences / Statistical methods / Data processing fast Structural equation modeling fast Datenverarbeitung Sozialwissenschaften Structural equation modeling Social sciences Statistical methods Data processing Strukturgleichungsmodell (DE-588)4252999-2 gnd rswk-swf Strukturgleichungsmodell (DE-588)4252999-2 s DE-604 Erscheint auch als Druck-Ausgabe (hbk.) 978-1-4625-2335-1 Erscheint auch als Druck-Ausgabe (pbk.) 978-1-4625-2334-4 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029434177&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Kline, Rex B. Principles and practice of structural equation modeling MATHEMATICS / Applied bisacsh MATHEMATICS / Probability & Statistics / General bisacsh Social sciences / Statistical methods / Data processing fast Structural equation modeling fast Datenverarbeitung Sozialwissenschaften Structural equation modeling Social sciences Statistical methods Data processing Strukturgleichungsmodell (DE-588)4252999-2 gnd |
| subject_GND | (DE-588)4252999-2 |
| title | Principles and practice of structural equation modeling |
| title_auth | Principles and practice of structural equation modeling |
| title_exact_search | Principles and practice of structural equation modeling |
| title_full | Principles and practice of structural equation modeling Rex B. Kline ; series editor's note by Todd D. Little |
| title_fullStr | Principles and practice of structural equation modeling Rex B. Kline ; series editor's note by Todd D. Little |
| title_full_unstemmed | Principles and practice of structural equation modeling Rex B. Kline ; series editor's note by Todd D. Little |
| title_short | Principles and practice of structural equation modeling |
| title_sort | principles and practice of structural equation modeling |
| topic | MATHEMATICS / Applied bisacsh MATHEMATICS / Probability & Statistics / General bisacsh Social sciences / Statistical methods / Data processing fast Structural equation modeling fast Datenverarbeitung Sozialwissenschaften Structural equation modeling Social sciences Statistical methods Data processing Strukturgleichungsmodell (DE-588)4252999-2 gnd |
| topic_facet | MATHEMATICS / Applied MATHEMATICS / Probability & Statistics / General Social sciences / Statistical methods / Data processing Structural equation modeling Datenverarbeitung Sozialwissenschaften Structural equation modeling Social sciences Statistical methods Data processing Strukturgleichungsmodell |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029434177&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT klinerexb principlesandpracticeofstructuralequationmodeling |