Foundations of Factor Analysis

By S. Mulaik. 2009

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Citations in the corpus

Only three factors of personality description are fully replicable across languages: a comparison of 14 trait taxonomies. (2010, background): “80 as thresholds below which factors are not considered identical (Haven & Ten Berge, 1977; Horn, Wanberg, & Appel, 1973; Lorenzo-Seva & Ten Berge, 2006; Mulaik, 1972; Van de Vijver & Leung, 1997).”
Current Methodological Considerations in Exploratory and Confirmatory Factor Analysis (2011, methodology): “Researchers often use MIs to modify CFA models, but when this occurs the perceived CFA becomes exploratory in nature (Bollen, 1989; Brown, 2001) and may be inappropriate (e.g., Asparouhov & Muthén, 2009; Byrne, 2001; Gerbing & Hamilton, 1996; Gorsuch, 1983; MacCallum et al., 1992; Marsh et al., 2011”
Estimation of oblique structure via penalized likelihood factor analysis (2013, methodology): “In some cases, however, analysts may prefer to relax the requirement that the common factors are orthogonal (e.g., Mulaik 1972).”
Common Beliefs and Reality About PLS (2014, methodology): “6 This is because component methods with multiple indicators achieve a degree of adjustment for unreliability, due to the very nature of weighted composites (e.g., Creager & Valentine, 1962; Ley, 1972; Mulaik, 2010; Rigdon, 2012).”
4. Algebraic Representations of Beliefs and Attitudes II: Microbelief Models for Dichotomous Belief Data (2000, background): “Most commonly, these latent variables are seen asfactors, as in factor analysis (Mulaik 1972; for an example, see Stimson 1975), or astraits, as in Item Response Theory (Rasch 1966, Birnbaum 1968; for examples, see Duncan 1984).”
Correlation and Causation in the Study of Personality (2012, methodology): “Factor-analytic models treat measured variables, such as the different items in a personality scale, as indicators of Copyright © 2012 John Wiley & Sons, Ltd. unmeasured quantitative variables called common factors (McDonald, 1985; Mulaik, 2010; Thomson, 1951).”
Mplus Short Courses Topic 1 Exploratory Factor Analysis, Confirmatory Factor Analysis, And Structural Equation Modeling For Continuous Outcomes (2009, background): “Mulaik, S. (1972). The foundations of factor analysis.”
Enhancing Interpretability in Factor Analysis by Means of Mathematical Optimization (2019, background): “EFA is a multivariate statistical method that brings into light the effects of (a small number of) latent variables, called factors, on a set of observed variables, Mulaik (2009), Spearman (1904) and Thurstone (1931).”
Fungible Weights in Multiple Regression (2008, background): “Imagine a cone suspended in space (see Mulaik, 1972, pp. 328 –329, for another example of how a cone can represent the geometry of correlational indeterminancy).”