Pinned Repositories
3-Step-ML-auto
This R tutorial automates the 3-step ML auxiliary variable procedure using the MplusAutomation package (Hallquist & Wiley, 2018) to estimate models and extract relevant parameters. To learn more about auxiliary variable integration methods and why multi-step methods are necessary for producing un-biased estimates see Asparouhov & Muthén (2014).
BCH-MplusAuto
This `R` tutorial automates the BCH two-step axiliary variable procedure (Bolk, Croon, Hagenaars, 2004) using the `MplusAutomation` package (Hallquist & Wiley, 2018) to estimate models and extract relevant parameters.
continued_training
immerse-ucsb.github.io
GH pages repository to host all tutorial scripts as websites for sharing (PDF/HTML formats).
interpret-aux-vars
Interpret & Summarize Auxiliary Variables. Two examples provided including a distal outcome model with control covariate & a moderation model.
intro-to-mplusautomation
This repo will go through how to use Mplus and MplusAutomation in R. For Part 1, we will first walk through how to run basic descriptive statistics using only Mplus. In Part 2, we will use an R package called MplusAutomation to run the same analysis as Part 1, only this time using only RStudio. Part 3 will go over data cleaning in R.
intro_to_rstudio
This walkthrough is presented by the IMMERSE team and will go through some common tasks carried out in R.
lca_enum
We utilize six focal indicators which constitute the latent class model in our example; three variables which report on harassment/bullying in schools based on disability, race, or sex, and three variables on full-time equivalent school staff hires (counselor, psychologist, law enforcement).
lpa_enum
This repository walks through latent profile analysis using `tidyLPA` and `MplusAutomation`.
quick-lca-mplusauto
Demonstrate the speed of running an LCA analysis using MplusAutomation
IMMERSE Project's Repositories
immerse-ucsb/3-Step-ML-auto
This R tutorial automates the 3-step ML auxiliary variable procedure using the MplusAutomation package (Hallquist & Wiley, 2018) to estimate models and extract relevant parameters. To learn more about auxiliary variable integration methods and why multi-step methods are necessary for producing un-biased estimates see Asparouhov & Muthén (2014).
immerse-ucsb/quick-lca-mplusauto
Demonstrate the speed of running an LCA analysis using MplusAutomation
immerse-ucsb/BCH-MplusAuto
This `R` tutorial automates the BCH two-step axiliary variable procedure (Bolk, Croon, Hagenaars, 2004) using the `MplusAutomation` package (Hallquist & Wiley, 2018) to estimate models and extract relevant parameters.
immerse-ucsb/growth-mixtures
immerse-ucsb/immerse-ucsb.github.io
GH pages repository to host all tutorial scripts as websites for sharing (PDF/HTML formats).
immerse-ucsb/intro_to_rstudio
This walkthrough is presented by the IMMERSE team and will go through some common tasks carried out in R.
immerse-ucsb/continued_training
immerse-ucsb/interpret-aux-vars
Interpret & Summarize Auxiliary Variables. Two examples provided including a distal outcome model with control covariate & a moderation model.
immerse-ucsb/intro-to-mplusautomation
This repo will go through how to use Mplus and MplusAutomation in R. For Part 1, we will first walk through how to run basic descriptive statistics using only Mplus. In Part 2, we will use an R package called MplusAutomation to run the same analysis as Part 1, only this time using only RStudio. Part 3 will go over data cleaning in R.
immerse-ucsb/lca_enum
We utilize six focal indicators which constitute the latent class model in our example; three variables which report on harassment/bullying in schools based on disability, race, or sex, and three variables on full-time equivalent school staff hires (counselor, psychologist, law enforcement).
immerse-ucsb/lpa_enum
This repository walks through latent profile analysis using `tidyLPA` and `MplusAutomation`.
immerse-ucsb/in-person-training-2024
In-person training materials for Cohort 2
immerse-ucsb/logistic_regression
Multinomial Logistic Regression
immerse-ucsb/po_LCA
immerse-ucsb/tidy_wrangling_practice