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index.rmd
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---
title: 'MixR: Mixed Models in R'
author: 'Ben Whalley'
date: "Feb 2021"
bibliography: [references.bib]
biblio-style: apa6
link-citations: yes
output:
webex::html_clean
---
```{r, include=F, echo=F}
knitr::opts_chunk$set(echo = TRUE,
collapse=TRUE,
comment=NA,
cache = TRUE,
message=FALSE)
```
# {-}
](images/cocktails.png)
------------------
> This short course aims to extend your existing skills, and give you confidence when
> working with and analysing repeated measures data. We use examples from typical
> experimental and applied studies in psychology. We cover repeat measures Anova
> designs, more general mixed-effects and random-slope models, and touch on Bayesian
> parameter estimation for mixed models. We also learn how to test specific hypotheses
> from mixed models.
# Sessions and worksheets
1. [Sources of variability](01-repeat-measures.html)
1. [Random effects models](02-mixed-models.html)
1. [Estimating and comparing](03-estimating.html)
# Approach
In common with all modules at Plymouth, we try to avoid the 'bag of tricks' approach to
teaching research methods and try to integrate new skills into a broader approach to
collecting and using data. Our workflow is inspired by Wickham's model for data science:
[Wickham, 2017](http://r4ds.had.co.nz/introduction.html):
In this option we do teach specific techniques, but the aim is always to help you
integrate this new knowledge into your own research practice.
# Access to R
Throughout the module we use R for data processing and analysis.
If you are taking this course at Plymouth University, the easiest way to run the code
examples here is to the school's RStudio Server.
- [Login to your account on the server here](https://rstudio.plymouth.ac.uk)
### Installing at home
If you want to install R on your own machine, instructions are available here:
- <https://github.com/plymouthPsychology/installR/>
Be sure to install the recommended packages or the examples given here won't work.
# License
All content on this site distributed under a
[Creative Commons](https://creativecommons.org/) licence. CC-BY-SA 4.0.