BEYOND SEM: GENERAL LATENT VARIABLE MODELING

By B. Muthén. 2002

1,126 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/46549618621297bf3a67c939469994c2816b449f

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In Management Science and Operations Research

In Statistics and Probability

Citations in the corpus

Covariates and Mixture Modeling: Results of a Simulation Study Exploring the Impact of Misspecified Effects on Class Enumeration (2016, background): “Some recommendations suggest including covariates at the onset of the modeling process, arguing that the additional information provided by the covariates might aid in reliable class enumeration (Li & Hser, 2011; Lubke & Muthén, 2007; Muthén, 2002).”
Shadow economies all over the world : new estimates for 162 countries from 1999 to 2007 (2010, background): “General overviews about the SEM approach are given in e.g. Hayduk (1987), Bollen (1989), Hoyle (1995), Maruyama (1997), Byrne (1998), Muthen (2002), Cziraky (2005).”
The Impact of Ignoring a Level of Nesting Structure in Multilevel Growth Mixture Models: A Monte Carlo Study (2010, background): “Instead, GMM allows within class random variation for the growth factors and the correlation between outcomes at all time points (Muthén, 2002).”
The Best of Both Worlds: Factor Analysis of Dichotomous Data Using Item Response Theory and Structural Equation Modeling (2003, methodology): “To define the measurement process and to take these errors into account, formal models with latent variables and multiple indicators are employed increasingly in all social science research areas (e.g., Bartholomew & Knott, 1999; Bollen, 1989, 2002; Loehlin, 1998; Muthén, 2002).”
Multiple-Group Analysis of Similarity in Latent Profile Solutions (2016, methodology): “Latent profile analyses (B. O. Muthén, 2002) were conducted based on the factor scores reflecting levels of AC, NC, and CC, using the robust maximum likelihood (MLR) estimator available in Morin et al. 241 Mplus 7.11 (L. K. Muthén & Muthén, 2013).”
A Multifoci Person-Centered Perspective on Workplace Affective Commitment: A Latent Profile/Factor Mixture Analysis (2011, methodology): “Recent developments in mixture modeling (e.g., Muthén, 2002; Muthén & Shedden, 1999; Vermunt & Magidson, 2002) offer interesting ways of circumventing those limits while remaining in line with the fundamental goal of cluster analyses.”
Profiles in self-regulated learning in the online learning environment (2010, methodology): “Latent class analyses may be considered a structural equation modeling approach to estimating 65 Profiles in Self-Regulated Learning in the Online Learning Environment Barnard-Brak, Lan, and Osland Paton unobserved heterogeneity via categorical latent variables (Muthén, 2002).”
Intervention Research in Social Work: Recent Advances and Continuing Challenges (2004, methodology): “Just reviewing statistical methods in a bare bones way, advances in variable-centered and person-centered analyses appear to be leading to a general latent structure perspective (Muthen, 2002).”
The Dynamics of Economic Disadvantage and Children's Life Chances (2006, methodology): “More information on the estimation of these models may be found in Jones et al. (2001), McLachlan and Peel (2000), Muthén (2001a, 2002, 2004), and Nagin (1999).”
Testing Measurement Invariance: A Comparison of Multiple-Group Categorical CFA and IRT (2011, methodology): “Diff test function in Mplus (Asparouhov & Muthén, 2006) allows the evaluation of robust chi-square difference between models. For the measurement invariance study, theta parameterization is optimal because the unique factor variances are freely estimated across multiple groups, so invariance of uniq”
Is creativity domain-specific? Latent class models of creative accomplishments and creative self-descriptions. (2009, neutral): “In the generalized latent variable modeling framework (Muthén, 2002; Skrondal & RabeHesketh, 2004), an exploratory factor analysis is a kind of latent variable model, in which latent variables (factors) explain the covariance of observed variables (items).”
The person-oriented approach: A short theoretical and practical guide (2014, methodology): “Variants of this approach are latent class analysis for analysing categorical data (Lazarsfeld & Henry, 1968) and latent profile analysis for analysing continuous data (Gibson, 1959; Muthén, 2002).”
Educational Measurement (4th ed.) (2009, background): “Given the rapid developments in generalized latent variable modeling of the past 20 years (e.g., Muthén, 2002) a wider scope would have been both possible and desirable.”
Loss of Power in Logistic, Ordinal Logistic, and Probit Regression When an Outcome Variable Is Coarsely Categorized (2006, background): “…depressed, nondepressed), it may be possible to develop latent class models that represent a continuous latent outcome variable (the probability that the participant is a member of the class) rather than a binary variable (the observed class of the participant; see Clogg, 1995; Muthén, 2002).”
Discernment and creativity: How well can people identify their most creative ideas? (2008, methodology): “Although typical multilevel models have only observed variables, this study estimated a general two-level model with both latent and observed variables (Muthén, 1997, 2002).”