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Exploratory and Confirmatory Factor Analysis: Understanding Concepts and Applications
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In this paper, the authors present the important concepts required for implementing two disciplines of factor analysis -exploratory factor analysis (EFA) and confirmatory Factor Analysis (CFA) with an emphasis on EFA/CFA linkages.Abstract:
This volume presents the important concepts required for implementing two disciplines of factor analysis - exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) with an emphasis on EFA/CFA linkages. Modern extensions of older data analysis methods (e.g., ANOVA, regression, MANOVA, and descriptive discriminant analysis) have brought theory-testing procedures to the analytic forefront. Variations of factor analysis, such as the factoring of people or time, have great potential to inform psychological research. Thompson deftly presents highly technical material in an appealing and accessible manner. The book is unique in that it presents both exploratory and confirmatory methods within the single category of the general linear model (GLM). Canons of best factor analytic practice are presented and explained. An actual data set, generated by 100 graduate students and 100 faculty from the United States and Canada, is used throughout the book, allowing readers to replicate reported results.read more
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Scale Development Research: A Content Analysis and Recommendations for Best Practices
TL;DR: The authors conducted a content analysis on new scale development articles appearing in the Journal of Counseling Psychology during 10 years (1995 to 2004) and uncovered a variety of specific practices that were at variance with the current literature on factor analysis or structural equation modeling, making recommendations for best practices in scale development research in counseling psychology using exploratory and confirmatory factor analysis.
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Exploratory factor analysis: A five-step guide for novices
TL;DR: The objective of the paper is to provide an exploratory factor analysis protocol, offering potential researchers with an empirically-supported systematic approach that simplifies the many guidelines and options associated with completing EFA.
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Reporting practices in confirmatory factor analysis: an overview and some recommendations.
TL;DR: Results indicate some positive findings with respect to reporting practices including proposing multiple models a priori and near universal reporting of the chi-square significance test, but many deficiencies were found such as lack of information regarding missing data and assessment of normality.
Posted Content
Lateral Collinearity and Misleading Results in Variance-Based SEM: An Illustration and Recommendations
Ned Kock,Gary S. Lynn +1 more
TL;DR: A new approach for the assessment of both vertical and lateral collinearity in variance-based structural equation modeling is proposed and demonstrated in the context of the illustrative analysis, showing that standard validity and reliability tests do not properly capture lateral collInearity.
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Assessing measurement model quality in PLS-SEM using confirmatory composite analysis
TL;DR: In this article, confirmatory composite analysis (CCA) is applied to confirm measurement models when using partial least squares structural equation modeling (PLS-SEM) to confirm both reflective and formative measurement models of established measures that are being updated or adapted to a different context.
References
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Cutoff criteria for fit indexes in covariance structure analysis : Conventional criteria versus new alternatives
Li-tze Hu,Peter M. Bentler +1 more
TL;DR: In this article, the adequacy of the conventional cutoff criteria and several new alternatives for various fit indexes used to evaluate model fit in practice were examined, and the results suggest that, for the ML method, a cutoff value close to.95 for TLI, BL89, CFI, RNI, and G...
Book
Applied multiple regression/correlation analysis for the behavioral sciences
TL;DR: In this article, the Mathematical Basis for Multiple Regression/Correlation and Identification of the Inverse Matrix Elements is presented. But it does not address the problem of missing data.
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Comparative fit indexes in structural models
TL;DR: A new coefficient is proposed to summarize the relative reduction in the noncentrality parameters of two nested models and two estimators of the coefficient yield new normed (CFI) and nonnormed (FI) fit indexes.
Book
Structural Equation Modeling With Mplus: Basic Concepts, Applications, And Programming
TL;DR: Structural Equation Models: The Basics using the EQS Program and testing for Construct Validity: The Multitrait-Multimethod Model and Change Over Time: The Latent Growth Curve Model.
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Significance tests and goodness of fit in the analysis of covariance structures
TL;DR: In this article, a general null model based on modified independence among variables is proposed to provide an additional reference point for the statistical and scientific evaluation of covariance structure models, and the importance of supplementing statistical evaluation with incremental fit indices associated with the comparison of hierarchical models.