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- ISBN
- 9781462515363
Über dieses Produkt
Product Identifiers
Publisher
Guilford Publications
ISBN-10
1462515363
ISBN-13
9781462515363
eBay Product ID (ePID)
201681688
Product Key Features
Number of Pages
462 Pages
Publication Name
Confirmatory Factor Analysis for Applied Research
Language
English
Subject
Probability & Statistics / General, Nursing / Research & Theory, Statistics
Publication Year
2015
Features
Revised
Type
Textbook
Subject Area
Mathematics, Education, Psychology, Medical
Series
Methodology in the Social Sciences Ser.
Format
Trade Paperback
Dimensions
Item Height
0.8 in
Item Weight
29.6 Oz
Item Length
10 in
Item Width
7 in
Additional Product Features
Edition Number
2
Intended Audience
Scholarly & Professional
LCCN
2014-040687
Reviews
Very helpful tables are used to summarize each step of a method or procedure....Chapter 3 is the heart of the textbook. It is a beautiful introduction to CFA....Summaries at the beginning and end of each chapter, an extensive number of substantive examples, figures and tables, appendices, software input and output files, as well as a sophisticated structure...make each chapter very easy to follow....Provides readers with clear recommendations and guidelines of how to deal with problems as well as a comprehensive overview of the most important aspects of CFA that an applied researcher should know. Given these outstanding qualities, I strongly believe that [this text] will continue to have a strong impact on applied researchers...and graduate students. The first edition has become a benchmark textbook in the field of introductory psychometrics, and the carefully revised second edition will widen its readership and make an impact very soon.
Dewey Edition
22
Illustrated
Yes
Dewey Decimal
150.1/5195354
Edition Description
Revised edition
Table Of Content
l. Introduction Uses of Confirmatory Factor Analysis Psychometric Evaluation of Test Instruments Construct Validation Method Effects Measurement Invariance Evaluation Why a Book on CFA? Coverage of the Book Other Considerations Summary 2. The Common Factor Model and Exploratory Factor Analysis Overview of the Common Factor Model Procedures of EFA Factor Extraction Factor Selection Factor Rotation Factor Scores Summary 3. Introduction to CFA Similarities and Differences of EFA and CFA Common Factor Model Standardized and Unstandardized Solutions Indicator Cross-Loadings/Model Parsimony Unique Variances Model Comparison Purposes and Advantages of CFA Parameters of a CFA Model Fundamental Equations of a CFA Model CFA Model Identification Scaling the Latent Variable Statistical Identification Guidelines for Model Identification Estimation of CFA Model Parameters Illustration Descriptive Goodness-of-Fit Indices Absolute Fit Parsimony Correction Comparative Fit Guidelines for Interpreting Goodness-of-Fit Indices Summary Appendix 3.1. Communalities, Model-Implied Correlations, and Factor Correlations in EFA and CFA Appendix 3.2. Obtaining a Solution for a Just-Identified Factor Model Appendix 3.3. Hand Calculation of FML for the Figure 3.8 Path Model 4. Specification and Interpretation of CFA Models An Applied Example of a CFA Measurement Model Model Specification Substantive Justification Defining the Metric of Latent Variables Data Screening and Selection of the Fitting Function Running CFA in Different Software Programs Model Evaluation Overall Goodness of Fit Localized Areas of Strain Interpretability, Size, and Statistical Significance of the Parameter Estimates Interpretation and Calculation of CFA Model Parameter Estimates CFA Models with Single Indicators Reporting a CFA Study Summary Appendix 4.1. Model Identification Affects the Standard Errors of the Parameter Estimates Appendix 4.2. Goodness of Model Fit Does Not Ensure Meaningful Parameter Estimates Appendix 4.3. Example Report of the Two-Factor CFA Model of Neuroticism and Extraversion 5. Model Revision and Comparison Goals of Model Respecification Sources of Poor-Fitting CFA Solutions
Synopsis
With its emphasis on practical and conceptual aspects, rather than mathematics or formulas, this accessible book has established itself as the go-to resource on confirmatory factor analysis (CFA). Detailed, worked-through examples drawn from psychology, management, and sociology studies illustrate the procedures, pitfalls, and extensions of CFA methodology. The text shows how to formulate, program, and interpret CFA models using popular latent variable software packages (LISREL, Mplus, EQS, SAS/CALIS); understand the similarities and differences between CFA and exploratory factor analysis (EFA); and report results from a CFA study. It is filled with useful advice and tables that outline the procedures. The companion website ( www.guilford.com/brown3-materials ) offers data and program syntax files for most of the research examples, as well as links to CFA-related resources. New to This Edition *Updated throughout to incorporate important developments in latent variable modeling. *Chapter on Bayesian CFA and multilevel measurement models. *Addresses new topics (with examples): exploratory structural equation modeling, bifactor analysis, measurement invariance evaluation with categorical indicators, and a new method for scaling latent variables. *Utilizes the latest versions of major latent variable software packages., With its emphasis on practical and conceptual aspects, rather than mathematics or formulas, this accessible book has established itself as the go-to resource on confirmatory factor analysis (CFA). Detailed, worked-through examples drawn from psychology, management, and sociology studies illustrate the procedures, pitfalls, and extensions of CFA ......, With its emphasis on practical and conceptual aspects, rather than mathematics or formulas, this accessible book has established itself as the go-to resource on confirmatory factor analysis (CFA). Detailed, worked-through examples drawn from psychology, management, and sociology studies illustrate the procedures, pitfalls, and extensions of CFA methodology. The text shows how to formulate, program, and interpret CFA models using popular latent variable software packages (LISREL, Mplus, EQS, SAS/CALIS); understand the similarities and differences between CFA and exploratory factor analysis (EFA); and report results from a CFA study. It is filled with useful advice and tables that outline the procedures. The companion website offers data and program syntax files for most of the research examples, as well as links to CFA-related resources. New to This Edition Updated throughout to incorporate important developments in latent variable modeling. Chapter on Bayesian CFA and multilevel measurement models. Addresses new topics (with examples): exploratory structural equation modeling, bifactor analysis, measurement invariance evaluation with categorical indicators, and a new method for scaling latent variables. Utilizes the latest versions of major latent variable software packages.
LC Classification Number
BF39.2.F32B76 2015
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