Book Review: Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis (4th ed.)

By Kusum Singh. 2006

159 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/675c670f015500a96db9761b5dc98420ef01d440

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Citations in the corpus

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.”
Race, Poverty and SAT Scores: Modeling the Influences of Family Income on Black and White High School Students’ SAT Performance (2013, methodology): “An RMSEA of 0.05 or less and a CFI or TLI of 0.95 or higher indicate a close fit and plausible model (Bollen, 1989; Kline, 2005; Loehlin, 2004; Raykov & Marcoulides, 2006).”
Statistical and Practical Concerns With Published Communication Research Featuring Structural Equation Modeling (2017, background): “Loehlin (2004) gives this good advice: There is no reason to ritualistically drop every path that is nonsignificant.”
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).”
Psychiatric Symptomatology as a Predictor of Cyberbullying among University Students (2009, background): “Thus, the lower mean indicates a higher possibility. analysis provides a better framework than multiple regression for specifying a particular theoretical model regarding the relationship among a set of exogenous and endogenous variables (Kline, 2005; Loehlin, 2004).”
Narcissism in Organizations: A Multisource Appraisal Reflects Different Perspectives (2008, background): “General rules of thumb suggest that CFI and NNFI values between .90 and .95 indicate acceptable model fit, and values above .95 indicate good fit (Loehlin, 2004).”
Differences in Life Satisfaction and School Satisfaction Among Adolescents From Three Nations: The Role of Perceived Autonomy Support (2011, methodology): “Because our model is just-identified (Loehlin, 2004), the model fit C1 (Korea vs.”
Association of Pre-Service Teachers' Performance, Personality, and Beliefs with Teacher Self-Efficacy at Program Completion. (2012, methodology): “The consistency between the data and the theoretical model in this method is referred to as the goodness of fit, and can be assessed using an array of fit indices and the chi-square test statistic (Loehlin, 2004).”
A Meta-analysis of the Longitudinal Relationship Between Academic Self-Concept and Academic Achievement (2021, methodology): “With reference to the assumptions of Classical Test Theory, a combination of answers to two or more questions might provide a more accurate estimate of the latent variable behind these manifest variables (Hair et al., 1998; Loehlin, 2004).”
Appraisal components and emotion traits: Examining the appraisal basis of trait curiosity (2008, methodology): “As before, the mediational model was evaluated by comparing the path model to a model in which the direct effect is fixed at zero (Loehlin, 2004).”
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 ”