Confirmatory factor analysis for applied research:
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
New York [u.a.]
Guilford Press
2006
|
| Series: | Methodology in the social sciences
|
| Subjects: | |
| Online Access: | Table of contents Contributor biographical information Inhaltsverzeichnis Klappentext |
| Physical Description: | XVIII, 475 S. graph. Darst. |
| ISBN: | 1593852754 1593852746 9781593852740 9781593852757 |
Staff View
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| 245 | 1 | 0 | |a Confirmatory factor analysis for applied research |c Timothy A. Brown |
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Record in the Search Index
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Contents
1 • Introduction 1
Uses of Confirmatory Factor Analysis / 1
Psychometric Evaluation of Test Instruments I 1
Construct Validation I 2
Method Effects I 3
Measurement Invariance Evaluation I 4
Why a Book on CFA? / 5
Coverage of the Book / 6
Other Considerations / 8
Summary / 11
2 • The Common Factor Model 12
and Exploratory Factor Analysis
Overview of the Common Factor Model / 12
Procedures of EFA / 20
Factor Extraction I 21
Factor Selection I 23
Factor Rotation I 30
Factor Scores I 36
Summary / 37
3 • Introduction to CFA 40
Similarities and Differences of EFA and CFA / 40
Common Factor Model I 40
Standardized and Unstandardized Solutions I 41
Indicator Cross-Loadings/Model Parsimony I 42
Unique Variances I 46
Model Comparison I 47
xv
xvi Contents
Purposes and Advantages of CFA / 49
Parameters of a CFA Model / 53
Fundamental Equations of a CFA Model / 59
CFA Model Identification / 62
Scaling the Latent Variable I 62
Statistical Identification I 63
Guidelines for Model Identification I 71
Estimation of CFA Model Parameters / 72
Illustration I 76
Descriptive Goodness-of-Fit Indices / 81
Absolute Fit I 82
Parsimony Correction I 83
Comparative Fit I 84
Guidelines for Interpreting Goodness-of-Fit Indices I 86
Summary / 88
Appendix 3.1. Communalities, Model-Implied Correlations, and Factor
Correlations in EFA and CFA / 90
Appendix 3.2. Obtaining a Solution for a Just-Identified Factor Model / 93
Appendix 3.3. Hand Calculation of FML for the Figure 3.8 Path Model / 96
4 • Specification and Interpretation of CFA Models 103
An Applied Example of a CFA Measurement Model / 103
Model Specification / 106
Substantive Justification I 106
Defining the Metric of Latent Variables I 106
Data Screening and Selection of the Fitting Function / 107
Running the CFA Analysis / 108
Model Evaluation / 113
Overall Goodness of Fit I 113
Localized Areas of Strain I 114
Residuals I 115
Modification Indices I 119
Unnecessary Parameters I 124
Interpretability, Size, and Statistical Significance of the Parameter
Estimates I 126
Interpretation and Calculation of CFA Model Parameter
Estimates / 132
CFA Models with Single Indicators / 138
Reporting a CFA Study / 144
Summary / 148
Appendix 4.1. Model Identification Affects the Standard Errors of the
Parameter Estimates / 150
Appendix 4.2. Goodness of Model Fit Does Not Ensure Meaningful Parameter
Estimates / 153
Appendix 4.3. Example Report of the Two-Factor CFA Model of Neuroticism
and Extraversion / 155
Contents xvii
5 • CFA Model Revision and Comparison 157
Goals of Model Respecification / 157
Sources of Poor-Fitting CFA Solutions / 159
Number of Factors I 159
Indicators and Factor Loadings I 167
Correlated Errors I 181
Improper Solutions and TStonpositive Definite Matrices I 187
EFA in the CFA Framework / 193
Model Identification Revisited / 202
Equivalent CFA Solutions / 203
Summary / 209
6 • CFA of Multitrait-Multimethod Matrices 212
Correlated versus Random Measurement Error Revisited / 212
The Multitrait-Multimethod Matrix / 213
CFA Approaches to Analyzing the MTMM Matrix / 217
Correlated Methods Models I 218
Correlated Uniqueness Models I 220
Advantages and Disadvantages of Correlated Methods and
Correlated Uniqueness Models / 227
Other CFA Parameterizations of MTMM Data / 229
Consequences of Not Modeling Method Variance and
Measurement Error / 231
Summary / 233
7 • CFA with Equality Constraints, 236
Multiple Groups, and Mean Structures
Overview of Equality Constraints / 237
Equality Constraints within a Single Group / 238
Congeneric, Tau-Equivalent, and Parallel Indicators I 238
Longitudinal Measurement Invariance I 252
CFA in Multiple Groups / 266
Overview of Multiple-Groups Solutions I 266
Multiple-Groups CFA I 268
Selected Issues in Single- and Multiple-Groups CFA Invariance
Evaluation I 299
MIMIC Models (CFA with Covariates) I 304
Summary / 316
Appendix 7.1. Reproduction of the Observed Variance-Covariance Matrix with
Tau-Equivalent Indicators of Auditory Memory / 318
xviii Contents
8 • Other Types of CFA Models: 320
Higher-Order Factor Analysis, Scale Reliability
Evaluation, and Formative Indicators
Higher-Order Factor Analysis / 320
Second-Order Factor Analysis I 322
Schmid-Leiman Transformation I 334
Scale Reliability Estimation / 337
Point Estimation of Scale Reliability I 337
Standard Error and Interval Estimation of Scale Reliability I 345
Models with Formative Indicators / 351
Summary / 362
9 • Data Issues in CFA: 363
Missing, Non-Normal, and Categorical Data
CFA with Missing Data / 363
Mechanisms of Missing Data I 364
Conventional Approaches to Missing Data I 365
Recommended Missing Data Strategies I 367
CFA with Non-Normal or Categorical Data / 378
Non-Normal, Continuous Data I 379
Categorical Data I 387
Other Potential Remedies for Indicator Non-Normality I 404
Summary / 410
10* Statistical Power and Sample Size 412
Overview / 412
Satorra-Saris Method / 413
Monte Carlo Approach / 420
Summary and Future Directions in CFA / 429
Appendix 10.1. Monte Carlo Simulation in Greater Depth:
Data Generation / 434
References 439
Author Index 455
Subject Index 459
Web address for the author's data and computer files
and other resources: http://people.bu.edu/tabrown/
Emphasizing practical and theoretical aspects of
CFA
rather than mathematics or formu¬
las, Timothy A. Brown uses rich examples derived from the psychology, management,
and sociology literatures to provide in-depth treatment of the concepts, procedures, pit¬
falls, and extensions of
CFA
methodology. Chock full of useful advice and tables that outline
the procedures, the text shows readers how to conduct exploratory factor analysis (EFA) and
understand similarities to and differences from
CFA;
formulate, program, and interpret
CFA
models using popular latent variable software packages such as LISREL, Mplus, Amos, EQS,
and SAS/CALIS; and report results from
a CFA
study. Also covered are extensions of
CFA
to
traditional
IRT
analysis, methods for determining necessary sample sizes, and new
CFA
mod¬
eling possibilities, including multilevel factor models and factor mixture models. Special fea¬
tures include a Web page offering data and program syntax files for many of the research
examples, as well as links to CFA-related resources. |
| adam_txt |
Contents
1 • Introduction 1
Uses of Confirmatory Factor Analysis / 1
Psychometric Evaluation of Test Instruments I 1
Construct Validation I 2
Method Effects I 3
Measurement Invariance Evaluation I 4
Why a Book on CFA? / 5
Coverage of the Book / 6
Other Considerations / 8
Summary / 11
2 • The Common Factor Model 12
and Exploratory Factor Analysis
Overview of the Common Factor Model / 12
Procedures of EFA / 20
Factor Extraction I 21
Factor Selection I 23
Factor Rotation I 30
Factor Scores I 36
Summary / 37
3 • Introduction to CFA 40
Similarities and Differences of EFA and CFA / 40
Common Factor Model I 40
Standardized and Unstandardized Solutions I 41
Indicator Cross-Loadings/Model Parsimony I 42
Unique Variances I 46
Model Comparison I 47
xv
xvi Contents
Purposes and Advantages of CFA / 49
Parameters of a CFA Model / 53
Fundamental Equations of a CFA Model / 59
CFA Model Identification / 62
Scaling the Latent Variable I 62
Statistical Identification I 63
Guidelines for Model Identification I 71
Estimation of CFA Model Parameters / 72
Illustration I 76
Descriptive Goodness-of-Fit Indices / 81
Absolute Fit I 82
Parsimony Correction I 83
Comparative Fit I 84
Guidelines for Interpreting Goodness-of-Fit Indices I 86
Summary / 88
Appendix 3.1. Communalities, Model-Implied Correlations, and Factor
Correlations in EFA and CFA / 90
Appendix 3.2. Obtaining a Solution for a Just-Identified Factor Model / 93
Appendix 3.3. Hand Calculation of FML for the Figure 3.8 Path Model / 96
4 • Specification and Interpretation of CFA Models 103
An Applied Example of a CFA Measurement Model / 103
Model Specification / 106
Substantive Justification I 106
Defining the Metric of Latent Variables I 106
Data Screening and Selection of the Fitting Function / 107
Running the CFA Analysis / 108
Model Evaluation / 113
Overall Goodness of Fit I 113
Localized Areas of Strain I 114
Residuals I 115
Modification Indices I 119
Unnecessary Parameters I 124
Interpretability, Size, and Statistical Significance of the Parameter
Estimates I 126
Interpretation and Calculation of CFA Model Parameter
Estimates / 132
CFA Models with Single Indicators / 138
Reporting a CFA Study / 144
Summary / 148
Appendix 4.1. Model Identification Affects the Standard Errors of the
Parameter Estimates / 150
Appendix 4.2. Goodness of Model Fit Does Not Ensure Meaningful Parameter
Estimates / 153
Appendix 4.3. Example Report of the Two-Factor CFA Model of Neuroticism
and Extraversion / 155
Contents xvii
5 • CFA Model Revision and Comparison 157
Goals of Model Respecification / 157
Sources of Poor-Fitting CFA Solutions / 159
Number of Factors I 159
Indicators and Factor Loadings I 167
Correlated Errors I 181
Improper Solutions and TStonpositive Definite Matrices I 187
EFA in the CFA Framework / 193
Model Identification Revisited / 202
Equivalent CFA Solutions / 203
Summary / 209
6 • CFA of Multitrait-Multimethod Matrices 212
Correlated versus Random Measurement Error Revisited / 212
The Multitrait-Multimethod Matrix / 213
CFA Approaches to Analyzing the MTMM Matrix / 217
Correlated Methods Models I 218
Correlated Uniqueness Models I 220
Advantages and Disadvantages of Correlated Methods and
Correlated Uniqueness Models / 227
Other CFA Parameterizations of MTMM Data / 229
Consequences of Not Modeling Method Variance and
Measurement Error / 231
Summary / 233
7 • CFA with Equality Constraints, 236
Multiple Groups, and Mean Structures
Overview of Equality Constraints / 237
Equality Constraints within a Single Group / 238
Congeneric, Tau-Equivalent, and Parallel Indicators I 238
Longitudinal Measurement Invariance I 252
CFA in Multiple Groups / 266
Overview of Multiple-Groups Solutions I 266
Multiple-Groups CFA I 268
Selected Issues in Single- and Multiple-Groups CFA Invariance
Evaluation I 299
MIMIC Models (CFA with Covariates) I 304
Summary / 316
Appendix 7.1. Reproduction of the Observed Variance-Covariance Matrix with
Tau-Equivalent Indicators of Auditory Memory / 318
xviii Contents
8 • Other Types of CFA Models: 320
Higher-Order Factor Analysis, Scale Reliability
Evaluation, and Formative Indicators
Higher-Order Factor Analysis / 320
Second-Order Factor Analysis I 322
Schmid-Leiman Transformation I 334
Scale Reliability Estimation / 337
Point Estimation of Scale Reliability I 337
Standard Error and Interval Estimation of Scale Reliability I 345
Models with Formative Indicators / 351
Summary / 362
9 • Data Issues in CFA: 363
Missing, Non-Normal, and Categorical Data
CFA with Missing Data / 363
Mechanisms of Missing Data I 364
Conventional Approaches to Missing Data I 365
Recommended Missing Data Strategies I 367
CFA with Non-Normal or Categorical Data / 378
Non-Normal, Continuous Data I 379
Categorical Data I 387
Other Potential Remedies for Indicator Non-Normality I 404
Summary / 410
10* Statistical Power and Sample Size 412
Overview / 412
Satorra-Saris Method / 413
Monte Carlo Approach / 420
Summary and Future Directions in CFA / 429
Appendix 10.1. Monte Carlo Simulation in Greater Depth:
Data Generation / 434
References 439
Author Index 455
Subject Index 459
Web address for the author's data and computer files
and other resources: http://people.bu.edu/tabrown/
Emphasizing practical and theoretical aspects of
CFA
rather than mathematics or formu¬
las, Timothy A. Brown uses rich examples derived from the psychology, management,
and sociology literatures to provide in-depth treatment of the concepts, procedures, pit¬
falls, and extensions of
CFA
methodology. Chock full of useful advice and tables that outline
the procedures, the text shows readers how to conduct exploratory factor analysis (EFA) and
understand similarities to and differences from
CFA;
formulate, program, and interpret
CFA
models using popular latent variable software packages such as LISREL, Mplus, Amos, EQS,
and SAS/CALIS; and report results from
a CFA
study. Also covered are extensions of
CFA
to
traditional
IRT
analysis, methods for determining necessary sample sizes, and new
CFA
mod¬
eling possibilities, including multilevel factor models and factor mixture models. Special fea¬
tures include a Web page offering data and program syntax files for many of the research
examples, as well as links to CFA-related resources. |
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| id | DE-604.BV021558583 |
| illustrated | Illustrated |
| index_date | 2024-07-02T14:33:58Z |
| indexdate | 2024-07-20T07:39:35Z |
| institution | BVB |
| isbn | 1593852754 1593852746 9781593852740 9781593852757 |
| language | English |
| lccn | 2006001103 |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-014774562 |
| oclc_num | 611899080 |
| open_access_boolean | |
| owner | DE-20 DE-19 DE-BY-UBM DE-M382 DE-11 DE-355 DE-BY-UBR DE-384 DE-188 DE-N32 DE-29 DE-91 DE-BY-TUM DE-473 DE-BY-UBG |
| owner_facet | DE-20 DE-19 DE-BY-UBM DE-M382 DE-11 DE-355 DE-BY-UBR DE-384 DE-188 DE-N32 DE-29 DE-91 DE-BY-TUM DE-473 DE-BY-UBG |
| physical | XVIII, 475 S. graph. Darst. |
| publishDate | 2006 |
| publishDateSearch | 2006 |
| publishDateSort | 2006 |
| publisher | Guilford Press |
| record_format | marc |
| series2 | Methodology in the social sciences |
| spelling | Brown, Timothy A. 1960- Verfasser (DE-588)142620289 aut Confirmatory factor analysis for applied research Timothy A. Brown New York [u.a.] Guilford Press 2006 XVIII, 475 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Methodology in the social sciences Analyse factorielle Factoranalyse gtt Factor analysis Psychologie (DE-588)4047704-6 gnd rswk-swf Empirische Sozialforschung (DE-588)4014606-6 gnd rswk-swf Faktorenanalyse (DE-588)4016338-6 gnd rswk-swf Faktorenanalyse (DE-588)4016338-6 s Psychologie (DE-588)4047704-6 s 1\p DE-604 Empirische Sozialforschung (DE-588)4014606-6 s 2\p DE-604 http://www.loc.gov/catdir/toc/ecip066/2006001103.html Table of contents http://www.loc.gov/catdir/enhancements/fy0629/2006001103-b.html Contributor biographical information HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014774562&sequence=000004&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Augsburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014774562&sequence=000006&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Brown, Timothy A. 1960- Confirmatory factor analysis for applied research Analyse factorielle Factoranalyse gtt Factor analysis Psychologie (DE-588)4047704-6 gnd Empirische Sozialforschung (DE-588)4014606-6 gnd Faktorenanalyse (DE-588)4016338-6 gnd |
| subject_GND | (DE-588)4047704-6 (DE-588)4014606-6 (DE-588)4016338-6 |
| title | Confirmatory factor analysis for applied research |
| title_auth | Confirmatory factor analysis for applied research |
| title_exact_search | Confirmatory factor analysis for applied research |
| title_exact_search_txtP | Confirmatory factor analysis for applied research |
| title_full | Confirmatory factor analysis for applied research Timothy A. Brown |
| title_fullStr | Confirmatory factor analysis for applied research Timothy A. Brown |
| title_full_unstemmed | Confirmatory factor analysis for applied research Timothy A. Brown |
| title_short | Confirmatory factor analysis for applied research |
| title_sort | confirmatory factor analysis for applied research |
| topic | Analyse factorielle Factoranalyse gtt Factor analysis Psychologie (DE-588)4047704-6 gnd Empirische Sozialforschung (DE-588)4014606-6 gnd Faktorenanalyse (DE-588)4016338-6 gnd |
| topic_facet | Analyse factorielle Factoranalyse Factor analysis Psychologie Empirische Sozialforschung Faktorenanalyse |
| url | http://www.loc.gov/catdir/toc/ecip066/2006001103.html http://www.loc.gov/catdir/enhancements/fy0629/2006001103-b.html http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014774562&sequence=000004&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014774562&sequence=000006&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
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