Latent Curve Models: A Structural Equation Approach

By Alexander J. McNeil. 2007

345 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/9c8156c6e04369f86e4e6feb0382b8c5329cb5e3

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Citations in the corpus

Multivariate latent change modeling of developmental decline in academic intrinsic math motivation and achievement: Childhood through adolescence (2007, methodology): “…and incorporated into a latent change model in which they can also be studied, the model is more commonly referred to as a multivariate model (the term multivariate latent curve model is also used to define such a model, see Bollen & Curran, 2006; Duncan et al., 1999; Raykov & Marcoulides, 2006).”
The Efficacy of Common Fit Indices for Enumerating Classes in Growth Mixture Models When Nested Data Structure Is Ignored (2017, methodology): “curve modeling (LGCM; Bollen & Curran, 2006), latent class growth analysis (LCGA; Nagin, 1999), and GMM (B. Muthén, 2004).”
Mediation Models for Longitudinal Data in Developmental Research (2009, background): “The interested reader is referred to Bollen and Curran (2006) and Preacher, Wichman, MacCallum, and Briggs (2008; see also Grimm & Ram, this issue). LGM has intriguing potential for application in mediation analysis. For example, Cheong, MacKinnon, and Khoo (2003) describe a parallel process LGM tha”
Conceptual and methodological issues in studying school leadership effects as a reciprocal process (2011, neutral): “Therefore, a more robust way to specify reciprocal effects lies in the use of longitudinal panel designs in which variables are each measured on two or more different occasions (Bollen & Curran, 2006; Lazarsfeld & Fiske, 1938; Marsh & Craven, 2006; Williams & Podsakoff, 1989).”
Positive effects of promoting prosocial behavior in early adolescence (2014, methodology): “To examine a potential intervention effect, we employed a Latent Growth Curve approach (LGC; Bollen & Curran, 2006).”
The p Factor: One General Psychopathology Factor in the Structure of Psychiatric Disorders? (2014, background): “CFI values greater than .95 and TLI values greater than 0.95 indicate good fit; RMSEA scores less than .05 are considered good (Bollen & Curran, 2006).”