Before this session, please: * Install [faux](https://debruine.github.io/faux/) in R `devtools::install_github("debruine/faux")` * Install `tidyverse`, `lme4`, `afex`, `broom`, `broom.mixed`, `kableExtra` and `GGally` (from CRAN) * Look over the lessons [Simulating Data](https://debruine.github.io/tutorials/sim-data.html) and [Simulating Mixed Effects](https://debruine.github.io/tutorials/sim-lmer.html) * Download the files for these lessons - [01_sim_intro_code.Rmd](https://osf.io/2tsgd/) (intro with code & exercises with answers) - [01_sim_intro_stub.Rmd](https://osf.io/vpxhs/) (intro without code & exercises) - [03_sim_data_code.Rmd](https://osf.io/36tv9/download) (lesson 1 framework with code) - [03_sim_data_stub.Rmd](https://osf.io/2tqha/download) (lesson 1 framework without code) - [04_sim_lmer_code.Rmd](https://osf.io/3fpv4/download) (lesson 2 framework with code) - [04_sim_lmer_stub.Rmd](https://osf.io/7j94v/download) (lesson 2 framework without code) In the lessons, we'll be using tidyverse functions and pipes. Have a look at my [pipes tutorial](https://debruine.github.io/tutorials/pipes.html) if you've never used pipes and want a quick intro. Optional: * Download the [app](https://osf.io/h3uvn/files/) folder * Install `shiny`, `shinyjs`, and `shinydashboard` ### Resources * [Data Skills for Reproducible Science](https://psyteachr.github.io/msc-data-skills/) open source textbook introducing tidyverse for psychologists * [Understanding mixed effects models through data simulation](https://osf.io/3cz2e/) (preprint, code, and shiny apps)