My name is Adam Garber and I am a PhD student in Education at the University of California, Santa Barbara.The purpose of this website is to make SEM modeling accesible for applied researchers and students. My work focuses on finite mixture modeling in-line with my advisor Dr. Karen Nylund-Gibson’s research (Latent_Variable_Group). My other interests are Autism and Special Education Research. In particular, the benifits of physical activity for children with disabilities.
MplusAutomation} is used for creating organized project workflows (Hallquist & Wiley, 2018)
here} package allow for reproducibility across operating systems.
tidyverse}’s highly coherent functions are used whenever possible to increase accessibility for applied audiences (Wickham et al., 2019)
… instead of estimating SEM models with R packages?
lavaan} have significant limitations in their capacity for flexibly specifying the full range modeling approaches available in SEM software (i.e., Mplus). This includes the ability to specify categorical latent variables (LCA/LPA/LTA), multi-level models (MLM), non-normal outcomes (GLM), and their combinations (i.e., multi-level LTA with covariates & distals).
OpenMX} are less accessible to applied researchers.
… instead of doing all modeling entirely in Mplus?
Data examples: All lab exercises utilize public-use data repositories.
Hallquist, M. N., & Wiley, J. F. (2018). MplusAutomation: An R Package for Facilitating Large-Scale Latent Variable Analyses in Mplus. Structural equation modeling: a multidisciplinary journal, 25(4), 621-638.
Henry, K. L., & Muthén, B. (2010). Multilevel latent class analysis: An application of adolescent smoking typologies with individual and contextual predictors. Structural Equation Modeling, 17(2), 193-215.
Horst, A. (2020). Course & Workshop Materials. GitHub Repositories, https://https://allisonhorst.github.io/
Muthén, B. & Asparouhov, T. (2020). . Under review. Version 3.
Muthén, L.K. and Muthén, B.O. (1998-2017). Mplus User’s Guide. Eighth Edition. Los Angeles, CA: Muthén & Muthén
Muthén, L. K., & Muthén, B. O. (2002). Structural equation modeling, 9(4), 599-620.
R Core Team (2017). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/
Wickham et al., (2019). Welcome to the tidyverse. Journal of Open Source Software, 4(43), 1686, https://doi.org/10.21105/joss.01686