Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis

By J. Loehlin. 2003

1,213 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/35d739428c29056fc9d6050eca7c3f5df8ed866b

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Citations in the corpus

Sport sponsorship: The relationship between team loyalty, sponsorship awareness, attitude toward the sponsor, and purchase intentions (2013, methodology): “The model’s invariance was tested by comparing the unconstrained model with the model constraining the structural weights (Loehlin, 2003).”
Creativity and Intelligence Revisited: A Latent Variable Analysis of Wallach and Kogan (1965) (2008, methodology): “The present research applied latent variable analysis, a sophisticated approach to multivariate data (Kline, 2005; Loehlin, 2004) that was unavailable to the original researchers, to assess the creativity–intelligence relationship.”
Reporting practices in confirmatory factor analysis: an overview and some recommendations. (2009, methodology): “This finding is of concern as analyzing a correlation matrix, depending upon the nature of the model and the software used, may lead to incorrect parameter estimates and even fit indices (Cudeck, 1989; MacCallum & Austin, 2000), and it is generally deemed inappropriate when studies involve multiple ”
Race, Poverty and SAT Scores: Modeling the Influences of Family Income on Black and White High School Students’ SAT Performance (2013, unknown): “95 or higher indicate a close fit and plausible model (Bollen, 1989; Kline, 2005; Loehlin, 2004; Raykov & Marcoulides, 2006).”
Riskier Tests of the Validity of the Bifactor Model of Psychopathology (2019, methodology): “Adequacy of model fit was determined on the basis of guidelines suggested in the literature and the comparison of TLI, RMSEA, SRMR, and BIC (see Loehlin, 2004; Markon & Krueger, 2006), although we present the χ2, CFI, and the Akaike information criterion (AIC) in the spirit of full disclosure.”
Development of the human interaction dimension of the Self‐Regulated Learning Questionnaire in asynchronous online learning environments (2009, methodology): “According to Loehlin (2004), RMSEA > .1 indicates a poor fit.”
Expanding Insights on the Diversity Climate–Performance Link: The Role of Workgroup Discrimination and Group Size (2014, methodology): “…in the literature, we set the cut-off value for the CFI to .90 (Meyers, Gamst, & Guarino 2006), for the RMSEA < .10 (Browne & Cudeck, 1993; Loehlin, 2004), T A B L E I I Measurement Model Comparison Measurement Model χ2 Δχ2 df CFI RMSEA SRMR Hypothesized model: Three-factor model 405.6…”
Love, Sex, and Crime: Adolescent Romantic Relationships and Offending (2008, result): “Chi-square tests for differences (Loehlin 2004) indicate that a four-factor model—that separates sexual activity from substance use, crime, and love— significantly improves upon one-, two-, and three-factor models.24 These findings concur with those of Rodgers and Rowe (1990:283; see also Elliott…”