The itrackvalr package provides a collection of functions that make it easier to work with the various data sources used in value-based eye-tracking experiments.
TODO items
Plots for each tier of thresholding, such as 1.5 degrees and 2.5 degrees. Write summaries of how validation-revalidation participant groups look. Start a separate RMarkdown to generate per-idea summaries.
- What groups of participants are we using based on thresholds?
- How do we do dimensional reduction?
- Apply offsets to gx/gy THEN flip to consistent side for all participants
You must have R and RStudio installed on your computer.
Clone this repository into your local project folder using GitHub Desktop or via the command line using
git clone https://github.com/sokolhessnerlab/itrackvalr.gitThen, open the itrackvalr directory and double-click on itrackvalr.Rproj to launch the project in RStudio. When RStudio first loads the project, it will source the included .RProfile to configure helpful defaults for your session.
We use the renv package to manage packages used for developing and using itrackvalr. To install the package dependencies for this project, run the following restoration command in the R console.
renv::restore()The dependencies are tracked by version in the renv.lock file. If during development you install a package that the project will depend on to run properly, please use renv::snaptshot() to update the lock file.
For the current studies, participant data is stored on a shared drive at the University of Denver. If you plan to work with participant data during your session, you must connect to the data separately from this package from whichever machine you are working from.
If working remotely, a secure connection to participant data requires connecting to the DU VPN and then mounting the shared drive to your computer.
We are committed to fostering a welcoming community for the itrackvalr package.
View our Code of Conduct for our GitHub organization.
Please see our contributing guide.
Distributed under the MIT License. See LICENSE.md for more information.
Project Link: https://github.com/sokolhessnerlab/itrackvalr