A Semiparametric Approach to Modeling Nonlinear Relations Among Latent Variables

By Daniel J. Bauer. 2005

92 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/98514de2427b5d915a5ad60e9b2911c8701aba22

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Citations in the corpus

A Multifoci Person-Centered Perspective on Workplace Affective Commitment: A Latent Profile/Factor Mixture Analysis (2011, background): “In this context, care should be taken to avoid the reification of these profiles, as they are only heuristics (and should remain as such) that are useful to depict interactive patterns among multiple variables (Bauer, 2005; Bauer & Shanahan, 2007; Kreuter & Muthén, 2008).”
Estimating Latent Variable Interactions with the Unconstrained Approach: A Comparison of Methods to Form Product Indicators for Large, Unequal Numbers of Items (2011, methodology): “…methods of detecting latent interactions have done so using a small number, typically three to four, of indicators per exogenous factor or have been focused solely on cases where there was a 1:1 ratio between the indicators (e.g., Bauer, 2005; Klein & Moosbrugger, 2000; Marsh et al., 2004).”
Observations on the Use of Growth Mixture Models in Psychological Research (2007, methodology): “within the general GMM, Bauer & Curran (2003a) detected spurious class covariate interactions at a relatively high rate. B. Muthén (2004) provides an explanation of why this may occur: “[A] GGMM that incorrectly divides up trajectories in, say, low, medium and high classes might find that the covari”
An Alternative Approach for Nonlinear Latent Variable Models (2010, methodology): “Still other methods involve the use of sequential estimation ( Ping, 1996 ), factor scores ( Wall & Amemiya, 2003 ), and mixture models applied to obtain approximations to nonlinear models ( Bauer, 2005 ).”
A Nonlinear Structural Equation Mixture Modeling Approach for Nonnormally Distributed Latent Predictor Variables (2014, methodology): “…latent variables is the use of semiparametric structural equation mixture models (SEMM; Arminger & Stein, 1997; Arminger, Stein, & Wittenberg, 1999; Bauer, 2005; Bauer & Curran, 2004; Dolan & van der Maas, 1998; Jedidi, Jagpal, & DeSarbo, 1997a, 1997b; Muthen, 2001; Pek, Losardo, & Bauer, 2011;…”
Fitting Nonlinear Latent Growth Curve Models With Individually Varying Time Points (2014, methodology): “For semiparametric methods the presence of model error stemming from the use of an approximation is transparent (Bauer, 2005; Fan & Li, 2004), and they may often do an equal or better job of flexibly describing a functional form.”
On Insensitivity of the Chi-Square Model Test to Nonlinear Misspecification in Structural Equation Models (2008, methodology): “Finally, we mention Bauer (2005) where mixture models are applied to obtain approximations to nonlinear models.”