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Journal ArticleDOI

The limitations of model fit in comparing the bi-factor versus higher-order models of human cognitive ability structure

Aja Louise Murray, +1 more
- 01 Sep 2013 - 
- Vol. 41, Iss: 5, pp 407-422
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TLDR
In this article, the authors addressed the question of whether the bi-factor or higher-order model is the more appropriate model of human cognitive ability structure, and found that the comparison of bi-Factor and higher-Order models is substantially biased in favour of the Bi-factor model when, as is commonly the case in CFA analyses.
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This article is published in Intelligence.The article was published on 2013-09-01. It has received 242 citations till now. The article focuses on the topics: Model selection & Confirmatory factor analysis.

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A Bifactor Exploratory Structural Equation Modeling Framework for the Identification of Distinct Sources of Construct-Relevant Psychometric Multidimensionality

TL;DR: In this paper, two sources of construct-relevant psychometric multidimensionality present in many complex multidimensional instruments routinely used in psychological and educational research are related to the fallible nature of indicators as perfect indicators of a single construct, and the hierarchical nature of the constructs being assessed.
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Progress in achieving quantitative classification of psychopathology

Robert F. Krueger, +54 more
- 01 Oct 2018 - 
TL;DR: The aims and current foci of the HiTOP Consortium, a group of 70 investigators working together to study empirical classification of psychopathology, are described, which pertain to continued research on the empirical organization of psychopathological constructs; the connection between personality and psychopathology; the utility of empirically based psychopathology constructs in both research and the clinic.
Journal ArticleDOI

Three Concerns With Applying a Bifactor Model as a Structure of Psychopathology

TL;DR: However, this paper pointed out that strong correlations among measures may suggest a bifactor structure, that does not imply that such a structure exists at the genotypic level (e.g., Cohen, Cohen, Teresi, Marchi, & Velez, 1990).
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Using Bifactor Exploratory Structural Equation Modeling to Test for a Continuum Structure of Motivation

TL;DR: In this article, the authors explore the nature of workplace motivation by testing the continuum structure of motivation proposed by self-determination theory through the application of relatively new and advanced methodological techniques and demonstrate the usefulness of the overarching bifactor exploratory structural equation modeling framework in organizational psychology and discuss implications of such models over more traditional confirmatory factor analyses.
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Factor-Analytic Evidence for the Complexity of the Delis-Kaplan Executive Function System (D-KEFS).

TL;DR: The results show seven-factor solutions based on generalization of fixed weights to validation samples provided best estimates, which are consistent with process overlap theory, which suggest that complex tests are determined my many distinct executive processes.
References
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Journal ArticleDOI

Cutoff criteria for fit indexes in covariance structure analysis : Conventional criteria versus new alternatives

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

Using multivariate statistics

TL;DR: In this Section: 1. Multivariate Statistics: Why? and 2. A Guide to Statistical Techniques: Using the Book Research Questions and Associated Techniques.
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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.
Journal ArticleDOI

Evaluating the use of exploratory factor analysis in psychological research.

TL;DR: This paper reviewed the major design and analytical decisions that must be made when conducting exploratory factor analysis and notes that each of these decisions has important consequences for the obtained results, and the implications of these practices for psychological research are discussed.
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A rationale and test for the number of factors in factor analysis.

TL;DR: It is suggested that if Guttman's latent-root-one lower bound estimate for the rank of a correlation matrix is accepted as a psychometric upper bound, then the rank for a sample matrix should be estimated by subtracting out the component in the latent roots which can be attributed to sampling error.
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