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  1. quick-lca-mplusauto quick-lca-mplusauto Public

    Demonstrate the speed of running an LCA analysis using MplusAutomation

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  2. 3-Step-ML-auto 3-Step-ML-auto Public

    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 ab…

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  3. intro_to_rstudio intro_to_rstudio Public

    Forked from dinanajiarch/intro_to_rstudio

    This walkthrough is presented by the IMMERSE team and will go through some common tasks carried out in R.

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  4. BCH-MplusAuto BCH-MplusAuto Public

    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 …

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  5. immerse-ucsb.github.io immerse-ucsb.github.io Public template

    GH pages repository to host all tutorial scripts as websites for sharing (PDF/HTML formats).

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  6. lpa_enum lpa_enum Public

    This repository walks through latent profile analysis using `tidyLPA` and `MplusAutomation`.

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  • po_LCA Public
    immerse-ucsb/po_LCA’s past year of commit activity
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  • mini_topics Public
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  • immerse-ucsb.github.io Public template

    GH pages repository to host all tutorial scripts as websites for sharing (PDF/HTML formats).

    immerse-ucsb/immerse-ucsb.github.io’s past year of commit activity
    HTML 1 1 0 0 Updated Dec 11, 2024
  • immerse-ucsb/growth-mixtures’s past year of commit activity
    HTML 1 0 0 0 Updated Dec 2, 2024
  • lpa_enum Public

    This repository walks through latent profile analysis using `tidyLPA` and `MplusAutomation`.

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    HTML 1 0 0 0 Updated Nov 1, 2024
  • in-person-training-2024 Public

    In-person training materials for Cohort 2

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  • logistic_regression Public Forked from nkpizano/IMMERSE_Day-5

    Multinomial Logistic Regression

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    HTML 0 3 0 0 Updated May 21, 2024
  • intro-to-mplusautomation Public

    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.

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