README.md

In aineito/stats.VWP: Analysing visual world eye-tracking data in R

stats.VWP

Tutorials for visual world eye-tracking data analysis in R

Set up

Run the following commands to install this package. You need to have 'remotes' package installed before running them.

require(remotes)  # load 'remotes' 
remotes::install_github("aineito/stats.VWP")  # install 'stats.VWP' 

The package comes with 5 tutorials. You need to have 'learnr' package installed for the tutorials.

require(learnr)  # load 'learnr' 
require(stats.VWP)  # load 'stats.VWP' 

The GCA tutorial requires 'gazer' package, and the CPA tutorial requires the 'exchangr' and 'clusterperm'. They need to be installed from GitHub.

remotes::install_github("dmirman/gazer")  # install 'gazer'
remotes::install_github(c("dalejbarr/exchangr", "dalejbarr/clusterperm"))  # install 'exchangr' and 'clusterperm'

Other required packages can be installed by running the code below.

install.packages(c("Rmisc", "tidyverse", "ggplot2", "bdots", "ggnewscale", "permutes", "lme4", "boot", "mgcv", "itsadug", "buildmer", "permuco"))

You will also need Rtools to open the tutorials. You can download it from here: https://cran.r-project.org/bin/windows/Rtools/

Tutorials

You can open tutorials by running the following commands. Some of the tutorials may take some time to open (~ 5 min.).

learnr::run_tutorial("GCA", "stats.VWP") # Growth curve analysis
learnr::run_tutorial("CPA", "stats.VWP") # Cluster-based permutation analysis
learnr::run_tutorial("BDOTS", "stats.VWP") # Bootstrapped differences of timeseries
learnr::run_tutorial("GAMM", "stats.VWP") # Generalised additive modelling
learnr::run_tutorial("DPA", "stats.VWP") # Divergence point analysis

The tutorials below should still work, but they are a bit outdated and not being maintained.

learnr::run_tutorial("Session3", "stats.VWP") # visualising the data  
learnr::run_tutorial("Session4", "stats.VWP") # LME/GLMM analysis  
learnr::run_tutorial("Session6", "stats.VWP") # Growth curve analysis  
learnr::run_tutorial("Session9", "stats.VWP") # Cluster-based permutation analysis  
learnr::run_tutorial("Session11", "stats.VWP") # Divergence point analysis

aineito/stats.VWP documentation built on March 10, 2023, 4:44 p.m.