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https://github.com/mattansb/hierarchical-linear-models-for-psychologists

bgu-university easystats lme4 mixed-models psychologists rstats statistics tau-university teaching-materials
Last synced: 2 months ago
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Host: GitHub
URL: https://github.com/mattansb/hierarchical-linear-models-for-psychologists
Owner: mattansb
License: other
Created: 2024-09-26T12:40:36.000Z (3 months ago)
Default Branch: main
Last Pushed: 2024-09-26T12:40:38.000Z (3 months ago)
Last Synced: 2024-10-10T18:23:23.262Z (3 months ago)
Language: R
Size: 260 KB
Stars: 2
Watchers: 2
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE
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README

        

# Hierarchical Linear Models foR Psychologists

[![](https://img.shields.io/badge/Open%20Educational%20Resources-Compatable-brightgreen.png)](https://creativecommons.org/about/program-areas/education-oer/)

[![](https://img.shields.io/badge/CC-BY--NC%204.0-lightgray)](http://creativecommons.org/licenses/by-nc/4.0/)  

[![](https://img.shields.io/badge/Language-R-blue.png)](http://cran.r-project.org/)

_{*Last updated 2024-09-26.*}

This Github repo contains all lesson files for *Hierarchical Linear

Models in R*. The goal is to impart students with the basic tools to

construct, evaluate and compare various **(generalized) linear mixed

models, using

[`lme4`](https://cran.r-project.org/web/packages/lme4/index.html/)**,

based on Lesa Hoffman’s [*Longitudinal Analysis: Modeling Within-Person

Fluctuation and Change*](https://www.pilesofvariance.com/index.html).

(Materials developed with Yael Bar-Shachar.)

These topics were taught in the graduate-level course ***Hierarchical

Linear Models for Psychologists*** (Psych Dep., Ben-Gurion University of

the Negev; Psych Dep., Tel-Aviv University). This course assumes basic

competence in R (importing, regression modeling, plotting, etc.), along

the lines of [*Practical Applications in R for

Psychologists*](https://github.com/mattansb/Practical-Applications-in-R-for-Psychologists).

**Notes:**

- This repo contains only materials relating to *Practical Applications

  in R*, and does not contain any theoretical or introductory

  materials.  

- Please note that some code does not work *on purpose*, to force

  students to learn to debug.

## Setup

You will need:

1.  A fresh installation of [**`R`**](https://cran.r-project.org/)

    (preferably version 4.3.2 or above).

2.  [RStudio IDE](https://www.rstudio.com/products/rstudio/download/)

    (optional, but recommended).

3.  The following packages, listed by lesson:

| Lesson | Packages |

|----|----|

| [01 HLM Basics](.\01%20HLM%20Basics) | [`tidyverse`](https://CRAN.R-project.org/package=tidyverse), [`lmerTest`](https://CRAN.R-project.org/package=lmerTest), [`emmeans`](https://CRAN.R-project.org/package=emmeans), [`performance`](https://CRAN.R-project.org/package=performance), [`parameters`](https://CRAN.R-project.org/package=parameters), [`merDeriv`](https://CRAN.R-project.org/package=merDeriv), [`haven`](https://CRAN.R-project.org/package=haven), [`sjPlot`](https://CRAN.R-project.org/package=sjPlot), [`afex`](https://CRAN.R-project.org/package=afex) |

| [02 Model Comparisons](.\02%20Model%20Comparisons) | [`dplyr`](https://CRAN.R-project.org/package=dplyr), [`ggplot2`](https://CRAN.R-project.org/package=ggplot2), [`lmerTest`](https://CRAN.R-project.org/package=lmerTest), [`performance`](https://CRAN.R-project.org/package=performance), [`parameters`](https://CRAN.R-project.org/package=parameters), [`haven`](https://CRAN.R-project.org/package=haven), [`scales`](https://CRAN.R-project.org/package=scales), [`glue`](https://CRAN.R-project.org/package=glue), [`sjPlot`](https://CRAN.R-project.org/package=sjPlot), [`bayestestR`](https://CRAN.R-project.org/package=bayestestR) |

| [03 Cross level interactions and effect sizes](.\03%20Cross%20level%20interactions%20and%20effect%20sizes) | [`dplyr`](https://CRAN.R-project.org/package=dplyr), [`datawizard`](https://CRAN.R-project.org/package=datawizard), [`ggplot2`](https://CRAN.R-project.org/package=ggplot2), [`lmerTest`](https://CRAN.R-project.org/package=lmerTest), [`performance`](https://CRAN.R-project.org/package=performance), [`parameters`](https://CRAN.R-project.org/package=parameters), [`marginaleffects`](https://CRAN.R-project.org/package=marginaleffects), [`scales`](https://CRAN.R-project.org/package=scales) |

| [04 Growth Models](.\04%20Growth%20Models) | [`dplyr`](https://CRAN.R-project.org/package=dplyr), [`ggplot2`](https://CRAN.R-project.org/package=ggplot2), [`lmerTest`](https://CRAN.R-project.org/package=lmerTest), [`parameters`](https://CRAN.R-project.org/package=parameters), [`performance`](https://CRAN.R-project.org/package=performance), [`marginaleffects`](https://CRAN.R-project.org/package=marginaleffects), [`haven`](https://CRAN.R-project.org/package=haven), [`scales`](https://CRAN.R-project.org/package=scales), [`glue`](https://CRAN.R-project.org/package=glue), [`nlme`](https://CRAN.R-project.org/package=nlme), [`glmmTMB`](https://CRAN.R-project.org/package=glmmTMB), [`brms`](https://CRAN.R-project.org/package=brms), [`remotes`](https://CRAN.R-project.org/package=remotes), [`mixedup`](https://CRAN.R-project.org/package=mixedup), [`loo`](https://CRAN.R-project.org/package=loo), [`posterior`](https://CRAN.R-project.org/package=posterior), [`bayestestR`](https://CRAN.R-project.org/package=bayestestR) |

| [05 Within-Person Fluctuation Models](.\05%20Within-Person%20Fluctuation%20Models) | [`tidyverse`](https://CRAN.R-project.org/package=tidyverse), [`datawizard`](https://CRAN.R-project.org/package=datawizard), [`lmerTest`](https://CRAN.R-project.org/package=lmerTest), [`performance`](https://CRAN.R-project.org/package=performance), [`parameters`](https://CRAN.R-project.org/package=parameters), [`haven`](https://CRAN.R-project.org/package=haven) |

| [06 GLMMs](.\06%20GLMMs) | [`tidyverse`](https://CRAN.R-project.org/package=tidyverse), [`lme4`](https://CRAN.R-project.org/package=lme4), [`performance`](https://CRAN.R-project.org/package=performance), [`parameters`](https://CRAN.R-project.org/package=parameters), [`marginaleffects`](https://CRAN.R-project.org/package=marginaleffects), [`haven`](https://CRAN.R-project.org/package=haven), [`insight`](https://CRAN.R-project.org/package=insight), [`scales`](https://CRAN.R-project.org/package=scales) |

| [07 Multilpe random factors](.\07%20Multilpe%20random%20factors) | [`dplyr`](https://CRAN.R-project.org/package=dplyr), [`ggplot2`](https://CRAN.R-project.org/package=ggplot2), [`patchwork`](https://CRAN.R-project.org/package=patchwork), [`lmerTest`](https://CRAN.R-project.org/package=lmerTest), [`performance`](https://CRAN.R-project.org/package=performance), [`parameters`](https://CRAN.R-project.org/package=parameters), [`marginaleffects`](https://CRAN.R-project.org/package=marginaleffects), [`mlmRev`](https://CRAN.R-project.org/package=mlmRev), [`forcats`](https://CRAN.R-project.org/package=forcats) |

| [08 ANOVA](.\08%20ANOVA) | [`dplyr`](https://CRAN.R-project.org/package=dplyr), [`ggplot2`](https://CRAN.R-project.org/package=ggplot2), [`lmerTest`](https://CRAN.R-project.org/package=lmerTest), [`datawizard`](https://CRAN.R-project.org/package=datawizard), [`emmeans`](https://CRAN.R-project.org/package=emmeans), [`afex`](https://CRAN.R-project.org/package=afex), [`car`](https://CRAN.R-project.org/package=car), [`effectsize`](https://CRAN.R-project.org/package=effectsize), [`patchwork`](https://CRAN.R-project.org/package=patchwork), [`performance`](https://CRAN.R-project.org/package=performance), [`statmod`](https://CRAN.R-project.org/package=statmod), [`see`](https://CRAN.R-project.org/package=see) |

| [09 Assumptions](.\09%20Assumptions) | [`tidyverse`](https://CRAN.R-project.org/package=tidyverse), [`lmerTest`](https://CRAN.R-project.org/package=lmerTest), [`performance`](https://CRAN.R-project.org/package=performance), [`DHARMa`](https://CRAN.R-project.org/package=DHARMa), [`scales`](https://CRAN.R-project.org/package=scales) |

You can install all the packages used by running:

    # in alphabetical order:

    pkgs <- c(

      "afex", "bayestestR", "brms", "car", "datawizard", "DHARMa",

      "dplyr", "effectsize", "emmeans", "forcats", "ggplot2", "glmmTMB",

      "glue", "haven", "insight", "lme4", "lmerTest", "loo", "marginaleffects",

      "merDeriv", "mixedup", "mlmRev", "nlme", "parameters", "patchwork",

      "performance", "posterior", "remotes", "scales", "see", "sjPlot",

      "statmod", "tidyverse"

    )

    install.packages(pkgs, dependencies = TRUE)

Package Versions

The package versions used here:

- `afex` 1.4-1 (*CRAN*)

- `bayestestR` 0.14.0 (*CRAN*)

- `brms` 2.21.0 (*CRAN*)

- `car` 3.1-2 (*CRAN*)

- `datawizard` 0.12.3 (*CRAN*)

- `DHARMa` 0.4.6 (*CRAN*)

- `dplyr` 1.1.4 (*CRAN*)

- `effectsize` 0.8.9 (*CRAN*)

- `emmeans` 1.10.4 (*CRAN*)

- `forcats` 1.0.0 (*CRAN*)

- `ggplot2` 3.5.1 (*CRAN*)

- `glmmTMB` 1.1.9 (*CRAN*)

- `glue` 1.7.0 (*CRAN*)

- `haven` 2.5.4 (*CRAN*)

- `insight` 0.20.4 (*CRAN*)

- `lme4` 1.1-35.5 (*CRAN*)

- `lmerTest` 3.1-3 (*CRAN*)

- `loo` 2.8.0 (*CRAN*)

- `marginaleffects` 0.22.0 (*CRAN*)

- `merDeriv` 0.2-4 (*CRAN*)

- `mixedup` 0.4.0 (*Github: m-clark/mixedup*)

- `mlmRev` 1.0-8 (*CRAN*)

- `nlme` 3.1-164 (*CRAN*)

- `parameters` 0.22.2 (*CRAN*)

- `patchwork` 1.3.0 (*CRAN*)

- `performance` 0.12.3 (*CRAN*)

- `posterior` 1.6.0 (*CRAN*)

- `remotes` 2.5.0 (*CRAN*)

- `scales` 1.3.0 (*CRAN*)

- `see` 0.9.0 (*CRAN*)

- `sjPlot` 2.8.16 (*CRAN*)

- `statmod` 1.5.0 (*CRAN*)

- `tidyverse` 2.0.0 (*CRAN*)