A primer on partial least squares structural equation modeling (PLS-SEM):
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| Main Authors: | , , , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Los Angeles
SAGE
[2022]
|
| Edition: | Third edition |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Item Description: | Includes bibliographical references and index |
| Physical Description: | XX, 363 Seiten Illustrationen, Diagramme |
| ISBN: | 9781544396408 |
Staff View
MARC
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| 245 | 1 | 0 | |a A primer on partial least squares structural equation modeling (PLS-SEM) |c Joe F. Hair, Jr. ; G. Tomas M. Hult ; Christian M. Ringle ; Marko Sarstedt |
| 250 | |a Third edition | ||
| 264 | 1 | |a Los Angeles |b SAGE |c [2022] | |
| 264 | 4 | |c ©2022 | |
| 300 | |a XX, 363 Seiten |b Illustrationen, Diagramme | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 500 | |a Includes bibliographical references and index | ||
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| 653 | 0 | |a Least squares | |
| 653 | 0 | |a Structural equation modeling | |
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Record in the Search Index
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BRIEF CONTENTS xi Preface About the Authors xviii Chapter 1 • An Introduction to Structural Equation Modeling Chapter 2 • Specifying the Path Modeland Examining Data 40 Chapter 3 • Path Model Estimation 85 Chapter 4 • Assessing PLS-SEM Results—Part I: Evaluation of the Reflective Measurement Models 109 Assessing PLS-SEM Results—Part II: Evaluation of the Formative Measurement Models 140 Assessing PLS-SEM Results—Part III: Evaluation of the Structural Model 186 Chapter 5 Chapter 6 • • 1 Chapter 7 • Mediator and Moderator Analysis 228 Chapter 8 • Outlook on Advanced Methods 271 Glossary 305 References 327 Index 352
DETAILED CONTENTS Preface About the Authors Chapter 1 · An Introduction to Structurat Equation Modeling 1 1 Chapter Preview What Is Structural Equation Modeling? 2 Considerations in Using Structural Equation Modeling 6 Composite Variables 6 Measurement 7 Measurement Scales 8 Coding Data Distributions Principles of Structural Equation Modeting 10 10 12 Path Modets With Latent Variabtes 12 Testing Theoreticat Relationships 13 Measurement Theory 14 Structural Theory 14 PLS-SEM, CB-SEM, and Regressions Based on Sum Scores 15 Considerations When Applying PLS-SEM 18 Key Characteristics of the PLS-SEM Method 18 Data Characteristics 24 Minimum Sample Size Requirement 24 Missing Value Treatment 27 Nonnormal Data 28 Scales of Measurement Secondary Data Model Characteristics Guidelines for Choosing Between PLS-SEM and CB-SEM Organization of Remaining Chapters Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings 28 28 30 31 32 34 36 36 36 37
Chapter 2 · Specifying the Path Model and Examining Data Chapter Preview Stage 1: Specifying the Structural Model Mediation Moderation Control Variables Stage 2: Specifying the Measurement Models Reflective and Formative Measurement Models Single-Item Measures and Sum Scores Higher-Order Constructs Stage 3: Data Collection and Examination Missing Data Suspicious Response Patterns Outliers Data Distribution Case Study Illustration—Specifying the PLS-SEM Model Application of Stage 1: Structural Model Specification Application of Stage 2: Measurement Model Specification Application of Stage 3: Data Collection and Examination Path Model Creation Using the SmartPLS Software 40 41 41 44 45 47 50 51 57 59 61 62 64 64 65 67 67 69 71 72 Summary 79 Review Questions 81 Critical Thinking Questions 82 Key Terms 82 Suggested Readings 83 Chapter 3 · Path Model Estimation 85 Chapter Preview 85 Stage 4: Model Estimation and the PLS-SEM Algorithm 86 How the Algorithm Works 86 Statistical Properties Algorithmic Options and Parameter Settings to Run the Algorithm 92 94 Results Case Study Illustration—PLS Path Model Estimation (Stage 4) Model Estimation Estimation Results 96 97 97 99 Summary Review Questions Ю5 Critical Thinking Questions Ю6 Key Terms ^пб Suggested Readings ^6
Chapter4 · Assessing PLS-SEM Results—Parti: Evaluation of the Reflective Measurement Models 109 Chapter Preview 109 Overview of Stage 5: Evaluation of Measurement Models 110 Stage 5a-. Assessing Results of Reflective Measurement Models 116 Step 1: Indicator Reliability Step 2: Internal Consistency Reliability Step 3: Convergent Validity Step 4: Discriminant Validity Case Study Illustration—Evaluation of the Reflective Measurement Models [Stage 5a) Running the PLS-SEM Algorithm Reflective Measurement Model Evaluation 117 118 120 120 127 127 128 Summary 136 Review Questions 137 Critical Thinking Questions 137 Key Terms 137 Suggested Readings 138 Chapter 5 · Assessing PLS-SEM Results—Partii: Evaluation of the Formative Measurement Models 140 Chapter Preview 140 Stage 5b: Assessing Results of Formative Measurement Models 141 Step 1: Assess Convergent Validity Step 2: Assess Formative Measurement Models for Collinearity Issues Step 3: Assess the Significance and Relevance of the Formative Indicators Bootstrapping Procedure 143 145 Concept 148 152 152 Bootstrap Confidence Intervals 156 Case Study Illustration—Evaluation of the Formative Measurement Models (Stage 5b) Extending the Simple Path Model Reflective Measurement Model Evaluation (Recap) Formative Measurement Model Evaluation Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings 159 159 169 171 182 183 183 184 184
Chapter 6 · Assessing PLS-SEM Results—Partiil: Evaluation of the Structural Model 186 Chapter Preview 186 Stage 6: Structural Model Results Evaluation 187 Step 1: Assess the Structural Model for Collinearity Step 2: Assess the Significance and Relevance of the Structural Model Relationships Step 3: Assess the Model's Explanatory Power Step 4: Assess the Model's Predictive Power Number of Folds Number of Repetitions Prediction Statistic Results Interpretation Treating Predictive Power Issues Step 5: Model Comparisons 191 192 194 196 198 199 200 201 204 205 Case Study Illustration—Evaluation of the Structural Model (Stage 6) 209 Summary 223 Review Questions 225 Critical Thinking Questions 225 Key Terms 225 Suggested Readings 226 Chapter 7 · Mediator and Moderator Analysis 228 Chapter Preview 228 Mediation 229 Introduction Measurement and Structural Model Evaluation in Mediation Analysis Types of Mediating Effects Testing Mediating Effects Multiple Mediation Case Study Illustration—Mediation Moderation 229 233 233 236 238 240 243 Introduction Types of Moderator Variables 243 245 Modeling Moderating Effects Creating the Interaction Term Product Indicator Approach 247 249 249 Orthogonalizing Approach Two-Stage Approach Guidelines for Creating the Interaction Term 250 251 253
Mode! Evaluation Results Interpretation Moderated Mediation and Mediated Moderation ΔΌύ ок/ 257 Case Study Illustration—Moderation 260 Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings 2^8 268 2^9 269 Chapter 8 · Outlook on Advanced Methods Chapter Preview Importance-Performance Map Analysis Necessary Condition Analysis Higher-Order Constructs Confirmatory Tetrad Analysis Examining Endogeneity Treating Observed and Unobserved Heterogeneity Multigroup Analysis Uncovering Unobserved Heterogeneity Measurement Model Invariance Consistent PLS-SEM Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings 271 271 273 276 277 281 285 286 287 290 294 296 298 300 301 301 ՅՕշ Glossary 305 References 227 Index |
| adam_txt |
BRIEF CONTENTS xi Preface About the Authors xviii Chapter 1 • An Introduction to Structural Equation Modeling Chapter 2 • Specifying the Path Modeland Examining Data 40 Chapter 3 • Path Model Estimation 85 Chapter 4 • Assessing PLS-SEM Results—Part I: Evaluation of the Reflective Measurement Models 109 Assessing PLS-SEM Results—Part II: Evaluation of the Formative Measurement Models 140 Assessing PLS-SEM Results—Part III: Evaluation of the Structural Model 186 Chapter 5 Chapter 6 • • 1 Chapter 7 • Mediator and Moderator Analysis 228 Chapter 8 • Outlook on Advanced Methods 271 Glossary 305 References 327 Index 352
DETAILED CONTENTS Preface About the Authors Chapter 1 · An Introduction to Structurat Equation Modeling 1 1 Chapter Preview What Is Structural Equation Modeling? 2 Considerations in Using Structural Equation Modeling 6 Composite Variables 6 Measurement 7 Measurement Scales 8 Coding Data Distributions Principles of Structural Equation Modeting 10 10 12 Path Modets With Latent Variabtes 12 Testing Theoreticat Relationships 13 Measurement Theory 14 Structural Theory 14 PLS-SEM, CB-SEM, and Regressions Based on Sum Scores 15 Considerations When Applying PLS-SEM 18 Key Characteristics of the PLS-SEM Method 18 Data Characteristics 24 Minimum Sample Size Requirement 24 Missing Value Treatment 27 Nonnormal Data 28 Scales of Measurement Secondary Data Model Characteristics Guidelines for Choosing Between PLS-SEM and CB-SEM Organization of Remaining Chapters Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings 28 28 30 31 32 34 36 36 36 37
Chapter 2 · Specifying the Path Model and Examining Data Chapter Preview Stage 1: Specifying the Structural Model Mediation Moderation Control Variables Stage 2: Specifying the Measurement Models Reflective and Formative Measurement Models Single-Item Measures and Sum Scores Higher-Order Constructs Stage 3: Data Collection and Examination Missing Data Suspicious Response Patterns Outliers Data Distribution Case Study Illustration—Specifying the PLS-SEM Model Application of Stage 1: Structural Model Specification Application of Stage 2: Measurement Model Specification Application of Stage 3: Data Collection and Examination Path Model Creation Using the SmartPLS Software 40 41 41 44 45 47 50 51 57 59 61 62 64 64 65 67 67 69 71 72 Summary 79 Review Questions 81 Critical Thinking Questions 82 Key Terms 82 Suggested Readings 83 Chapter 3 · Path Model Estimation 85 Chapter Preview 85 Stage 4: Model Estimation and the PLS-SEM Algorithm 86 How the Algorithm Works 86 Statistical Properties Algorithmic Options and Parameter Settings to Run the Algorithm 92 94 Results Case Study Illustration—PLS Path Model Estimation (Stage 4) Model Estimation Estimation Results 96 97 97 99 Summary Review Questions Ю5 Critical Thinking Questions Ю6 Key Terms ^пб Suggested Readings ^6
Chapter4 · Assessing PLS-SEM Results—Parti: Evaluation of the Reflective Measurement Models 109 Chapter Preview 109 Overview of Stage 5: Evaluation of Measurement Models 110 Stage 5a-. Assessing Results of Reflective Measurement Models 116 Step 1: Indicator Reliability Step 2: Internal Consistency Reliability Step 3: Convergent Validity Step 4: Discriminant Validity Case Study Illustration—Evaluation of the Reflective Measurement Models [Stage 5a) Running the PLS-SEM Algorithm Reflective Measurement Model Evaluation 117 118 120 120 127 127 128 Summary 136 Review Questions 137 Critical Thinking Questions 137 Key Terms 137 Suggested Readings 138 Chapter 5 · Assessing PLS-SEM Results—Partii: Evaluation of the Formative Measurement Models 140 Chapter Preview 140 Stage 5b: Assessing Results of Formative Measurement Models 141 Step 1: Assess Convergent Validity Step 2: Assess Formative Measurement Models for Collinearity Issues Step 3: Assess the Significance and Relevance of the Formative Indicators Bootstrapping Procedure 143 145 Concept 148 152 152 Bootstrap Confidence Intervals 156 Case Study Illustration—Evaluation of the Formative Measurement Models (Stage 5b) Extending the Simple Path Model Reflective Measurement Model Evaluation (Recap) Formative Measurement Model Evaluation Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings 159 159 169 171 182 183 183 184 184
Chapter 6 · Assessing PLS-SEM Results—Partiil: Evaluation of the Structural Model 186 Chapter Preview 186 Stage 6: Structural Model Results Evaluation 187 Step 1: Assess the Structural Model for Collinearity Step 2: Assess the Significance and Relevance of the Structural Model Relationships Step 3: Assess the Model's Explanatory Power Step 4: Assess the Model's Predictive Power Number of Folds Number of Repetitions Prediction Statistic Results Interpretation Treating Predictive Power Issues Step 5: Model Comparisons 191 192 194 196 198 199 200 201 204 205 Case Study Illustration—Evaluation of the Structural Model (Stage 6) 209 Summary 223 Review Questions 225 Critical Thinking Questions 225 Key Terms 225 Suggested Readings 226 Chapter 7 · Mediator and Moderator Analysis 228 Chapter Preview 228 Mediation 229 Introduction Measurement and Structural Model Evaluation in Mediation Analysis Types of Mediating Effects Testing Mediating Effects Multiple Mediation Case Study Illustration—Mediation Moderation 229 233 233 236 238 240 243 Introduction Types of Moderator Variables 243 245 Modeling Moderating Effects Creating the Interaction Term Product Indicator Approach 247 249 249 Orthogonalizing Approach Two-Stage Approach Guidelines for Creating the Interaction Term 250 251 253
Mode! Evaluation Results Interpretation Moderated Mediation and Mediated Moderation ΔΌύ ок/ 257 Case Study Illustration—Moderation 260 Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings 2^8 268 2^9 269 Chapter 8 · Outlook on Advanced Methods Chapter Preview Importance-Performance Map Analysis Necessary Condition Analysis Higher-Order Constructs Confirmatory Tetrad Analysis Examining Endogeneity Treating Observed and Unobserved Heterogeneity Multigroup Analysis Uncovering Unobserved Heterogeneity Measurement Model Invariance Consistent PLS-SEM Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings 271 271 273 276 277 281 285 286 287 290 294 296 298 300 301 301 ՅՕշ Glossary 305 References 227 Index |
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| author | Hair, Joseph F. 1944- Hult, G. Tomas M. 1967- Ringle, Christian M. 1974- Sarstedt, Marko 1979- |
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| author_facet | Hair, Joseph F. 1944- Hult, G. Tomas M. 1967- Ringle, Christian M. 1974- Sarstedt, Marko 1979- |
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| dewey-hundreds | 500 - Natural sciences and mathematics |
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| discipline | Soziologie Mathematik Wirtschaftswissenschaften |
| discipline_str_mv | Soziologie Mathematik Wirtschaftswissenschaften |
| edition | Third edition |
| format | Book |
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| index_date | 2024-07-03T18:11:05Z |
| indexdate | 2024-09-04T00:08:27Z |
| institution | BVB |
| isbn | 9781544396408 |
| language | English |
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| physical | XX, 363 Seiten Illustrationen, Diagramme |
| publishDate | 2022 |
| publishDateSearch | 2022 |
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| publisher | SAGE |
| record_format | marc |
| spelling | Hair, Joseph F. 1944- Verfasser (DE-588)135615828 aut A primer on partial least squares structural equation modeling (PLS-SEM) Joe F. Hair, Jr. ; G. Tomas M. Hult ; Christian M. Ringle ; Marko Sarstedt Third edition Los Angeles SAGE [2022] ©2022 XX, 363 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Includes bibliographical references and index Methode der partiellen kleinsten Quadrate (DE-588)4591652-4 gnd rswk-swf Methode der kleinsten Quadrate (DE-588)4038974-1 gnd rswk-swf Strukturgleichungsmodell (DE-588)4252999-2 gnd rswk-swf Least squares Structural equation modeling Methode der kleinsten Quadrate (DE-588)4038974-1 s Strukturgleichungsmodell (DE-588)4252999-2 s DE-604 Methode der partiellen kleinsten Quadrate (DE-588)4591652-4 s Hult, G. Tomas M. 1967- Verfasser (DE-588)128685832 aut Ringle, Christian M. 1974- Verfasser (DE-588)122291557 aut Sarstedt, Marko 1979- Verfasser (DE-588)136486576 aut Erscheint auch als Online-Ausgabe, epub 978-1-5443-9641-5 Erscheint auch als Online-Ausgabe, epub 978-1-5443-9642-2 Erscheint auch als Online-Ausgabe, pdf 978-1-5443-9633-0 Digitalisierung UB Bamberg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032877440&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Hair, Joseph F. 1944- Hult, G. Tomas M. 1967- Ringle, Christian M. 1974- Sarstedt, Marko 1979- A primer on partial least squares structural equation modeling (PLS-SEM) Methode der partiellen kleinsten Quadrate (DE-588)4591652-4 gnd Methode der kleinsten Quadrate (DE-588)4038974-1 gnd Strukturgleichungsmodell (DE-588)4252999-2 gnd |
| subject_GND | (DE-588)4591652-4 (DE-588)4038974-1 (DE-588)4252999-2 |
| title | A primer on partial least squares structural equation modeling (PLS-SEM) |
| title_auth | A primer on partial least squares structural equation modeling (PLS-SEM) |
| title_exact_search | A primer on partial least squares structural equation modeling (PLS-SEM) |
| title_exact_search_txtP | A primer on partial least squares structural equation modeling (PLS-SEM) |
| title_full | A primer on partial least squares structural equation modeling (PLS-SEM) Joe F. Hair, Jr. ; G. Tomas M. Hult ; Christian M. Ringle ; Marko Sarstedt |
| title_fullStr | A primer on partial least squares structural equation modeling (PLS-SEM) Joe F. Hair, Jr. ; G. Tomas M. Hult ; Christian M. Ringle ; Marko Sarstedt |
| title_full_unstemmed | A primer on partial least squares structural equation modeling (PLS-SEM) Joe F. Hair, Jr. ; G. Tomas M. Hult ; Christian M. Ringle ; Marko Sarstedt |
| title_short | A primer on partial least squares structural equation modeling (PLS-SEM) |
| title_sort | a primer on partial least squares structural equation modeling pls sem |
| topic | Methode der partiellen kleinsten Quadrate (DE-588)4591652-4 gnd Methode der kleinsten Quadrate (DE-588)4038974-1 gnd Strukturgleichungsmodell (DE-588)4252999-2 gnd |
| topic_facet | Methode der partiellen kleinsten Quadrate Methode der kleinsten Quadrate Strukturgleichungsmodell |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032877440&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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