B
Bengt Muthén
Researcher at University of California, Los Angeles
Publications - 193
Citations - 57458
Bengt Muthén is an academic researcher from University of California, Los Angeles. The author has contributed to research in topics: Latent variable model & Latent variable. The author has an hindex of 87, co-authored 188 publications receiving 50604 citations. Previous affiliations of Bengt Muthén include Johns Hopkins University & University of California.
Papers
More filters
Journal ArticleDOI
Deciding on the Number of Classes in Latent Class Analysis and Growth Mixture Modeling: A Monte Carlo Simulation Study
TL;DR: Whereas the Bayesian Information Criterion performed the best of the ICs, the bootstrap likelihood ratio test proved to be a very consistent indicator of classes across all of the models considered.
Journal ArticleDOI
Testing for the equivalence of factor covariance and mean structures: The issue of partial measurement invariance.
TL;DR: In this article, the LISREL confirmatory factor analytic (CFA) model has been used to test the invariance of measurement parameters and mean structures for multidimensional self-concept data from high school adolescents.
Journal ArticleDOI
Assessing Reliability and Stability in Panel Models
Journal ArticleDOI
Integrating Person-Centered and Variable-Centered Analyses: Growth Mixture Modeling With Latent Trajectory Classes
Bengt Muthén,Linda K. Muthén +1 more
TL;DR: This paper gives a brief overview of new methods that integrate variable- and person-centered analyses in a general latent variable modeling framework that expands traditional latent variables modeling by including not only continuous latent variables but also categorical latent variables.
Journal ArticleDOI
Auxiliary Variables in Mixture Modeling: Three-Step Approaches Using Mplus
Tihomir Asparouhov,Bengt Muthén +1 more
TL;DR: This article discusses alternatives to single-step mixture modeling for latent class predictor variables in several different settings, including latent class analysis, latent transition analysis, and growth mixture modeling.