Confirmatory Factor Analysis for Applied Research/ (Record no. 172794)

MARC details
000 -LEADER
fixed length control field 04868nam a2200145Ia 4500
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781593852740
040 ## - CATALOGING SOURCE
Transcribing agency CUS
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 150.15195354
Item number BRO/C
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Brown,Timothy A.
245 #0 - TITLE STATEMENT
Title Confirmatory Factor Analysis for Applied Research/
Statement of responsibility, etc. Timothy A. Brown
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc. New York:
Name of publisher, distributor, etc. The Guilford Press,
Date of publication, distribution, etc. 2006.
300 ## - PHYSICAL DESCRIPTION
Extent 474p.p.
505 ## - FORMATTED CONTENTS NOTE
Formatted contents note 1 • Introduction<br/>Uses of Confirmatory Factor Analysis<br/>Psychometric Evaluation of Test Instruments<br/>Construct Valiclation<br/>Method Effects<br/>Measurement Invariance Evaluation<br/>Why a Book on CPA?<br/>Coverage of the Book<br/>Other Considerations<br/>Summary<br/>2 • The Common Factor Model<br/>and Exploratory Factor Analysis<br/>Overview of the Common Factor Model<br/>Procedures of EFA<br/>Eactor Extraction<br/>Factor Selection<br/>Factor Rotation<br/>Eactor Scores<br/>Summary<br/>3 • Introduction to CFA<br/>Similarities and Differences of EFA and CFA<br/>Common Eactor Model<br/>Standardized and Unstandardized Solutions<br/>Indicator Cross-Loadings/Model Parsimony<br/>Unique Variances<br/>Model Comparison<br/>Purposes and /Vdvantages of CPA<br/>Parameters of a CPA Model<br/>Pundamental Equations of a CPA Model<br/>CPA Model Identification<br/>Scaling the Latent Variable<br/>Statistical Identification<br/>Gtiidelines for Model Identification<br/>Estimation of CPA Model Parameters<br/>Illustration<br/>Descriptive Goodness-of-Pit Indices<br/>Absolute Fit<br/>Parsimony Correction<br/>Comparative Fit<br/>Cuidelines for Interpreting Coodness-of-Fit Indices<br/>Summary<br/>Appendix 3.1. Communalilics, Model-Implied Correlalion.s, and Factor<br/>Correlations in EPA and CPA<br/>Appendix 3.2. Obtainitig a Solution for a Just-Identified Factor Model<br/>Appendix 3.3. Hand Calculation of for the Figure 3.8 Path Model<br/>4 • Specification and Interpretation of CPA Models<br/>An Applied Example of a CPA Measurement Model<br/>Model Specification<br/>Sidistantive Justification<br/>Defining the Metric of Latent Variables<br/>Data Screening and Selection of the Pitting Punction<br/>Running the CPA Analysis<br/>Model Evaluation<br/>Overall Coodness of Fit<br/>Localized Areas of Strain<br/>Residuals<br/>Modification Indices<br/>Unnecessary Parametei s<br/>Intelprctability. Size, and Statistical Significance of the Parameter<br/>Estimates<br/>Interpretation and Calculation of CPA Model Parameter<br/>Estimates<br/>CPA Models with Single Indicators<br/>Reporting a Cf*A Study<br/>Sutnmary<br/>Appendix 4.1 . Model Identification Affects the Standard Errors of the<br/>Paratncter Pstitrtaics<br/>Appendix 4.2. Cioodncss of Model Fit Docs Not Pnsutc Meaningful Paratncter<br/>Estimates<br/>Appendix 4.3. Example Report of the fwo-Factor CPA Model of Ncuroticism<br/>and Extraversion<br/>5 • CFA Model Revision and Comparison<br/>Goals of Model Respecification<br/>Sources of Poor-Fitting CFA Solutions<br/>Number of Factors<br/>Indicators and Factor Loadings<br/>Correlated Errors<br/>Improper Solutions and Nonpositive Definite Matrices<br/>EFA in the CFA Framework<br/>Model Identification Revisited<br/>Equivalent CEA Solutions<br/>Summary<br/>6 • CFA of Muititraif^Multimethod Matrices<br/>Correlated versus Random Measurement Error Revisited<br/>The Multitrait-Multimethod Matrix<br/>CEA Approaches to Analyzing the MTMM Matrix<br/>Correlated Methods Models<br/>Correlated Unicjuencss Models<br/>Advantages and Disadvantages of Correlated Methods and<br/>Correlated Uniqueness Models<br/>Other CFA Parameterizations of MTMM Data<br/>Consequences of Not Modeling Method Variance and<br/>Measurement Error<br/>Summary<br/>7 • CFA with Equality Constraints,<br/>Multiple Groups, and Mean Structures<br/>Overview of Equality Constraints<br/>Equality Constraints within a Single Croup<br/>Congeneric, Tau-Eqiiivalcnt, and Parallel Indicators<br/>Longitudinal Measurement Invariance<br/>CFA in Multiple Croups<br/>Overview of Multiple-Groups Solutions<br/>Multiple-Groups CFA<br/>Selected Issues in Single- and Multiple-Groups CFA Invariance<br/>Evaluation<br/>MIMIC Models (CFA with Covariates)<br/>Summary<br/>Appendix 7.1. Reproduction of the Observed Variance-Covariance Matrix with<br/>Tau-Equivalent Indicators of Auditory Memory<br/>8 • Other Types of CPA Models:<br/>Higher-Order Factor Analysis, Scale Reliability<br/>Evaluation, and Formative Indicators<br/>Higher-Order Factor Analysis<br/>Sccond-Ordcr Factor Analysis<br/>Schmid-Lciman Transformation<br/>Scale Reliability Estimation<br/>Point Estimation oj Scale Reliability<br/>Standard Error and Intenal Estimation of Scale Reliahilitv<br/>Models with Formative Indicators<br/>Summar\'<br/>• Data issues in CPA:<br/>Missing, Non-Normal, and Categorical Data<br/>CPA with Missing Data<br/>Mechanisms of Missing Data<br/>Conventional Approaches to Missing Data<br/>Recommended Missing Data Strategies<br/>CPA with Non-Normal or Categorical Data<br/>Non-Normal, Continuous Data<br/>Categorical Data<br/>Othet Potential Remedies for Indicator Non-Normality<br/>Summary<br/>10 • Statistical Power and Sample Size<br/>Overview<br/>Satorra-Saris Method<br/>Monte Carlo Approach<br/>Summary and Future Directions in CPA<br/>Appendix 10.1. Monte Carlo Simulation in Greater Depth:<br/>Data Generation
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        Central Library, Sikkim University Central Library, Sikkim University General Book Section 29/08/2016 150.15195354 BRO/C P27774 29/08/2016 General Books
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