https://github.com/nathancooperjones/nsf-stress-study-files
For the NSF-sponsored CPL research.
https://github.com/nathancooperjones/nsf-stress-study-files
Last synced: 2 months ago
JSON representation
For the NSF-sponsored CPL research.
- Host: GitHub
- URL: https://github.com/nathancooperjones/nsf-stress-study-files
- Owner: nathancooperjones
- Created: 2018-08-06T18:23:57.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2018-09-18T15:18:10.000Z (over 6 years ago)
- Last Synced: 2025-02-10T22:29:20.255Z (4 months ago)
- Language: HTML
- Homepage: http://cpl.uh.edu/index.php
- Size: 116 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# CPL scripts for the NSF-funded Stress Study
Welcome to this Github repository, hosted by yours truly! There are a lot of files here, and I'm sure you are eager to get started! Well, hold your horses and let me tell you the intended order to at least get started:
1) The first thing you will have to run is `SplitSessions.R` to find all the subjects and create `*_merged.csv` files. We will use this in step #2.
2) Now we use that in `All-Subjects.Rmd` to generate a full dataframe that contains every single subjects' filtered measurements entitled `full_df.csv`. It is a great dataframe - in fact, it is so great that nearly every other script is based off of it. Neat, right!
3) More dataframes?! Yes! Now run `Hypothesis-Testing-Full-Sensor-Set.Rmd` to generate a dataframe that contains mean, normalized differences for all subjects' measurements. You'll need this for a few other scripts, most notably `Advanced-Analysis.R`.
4) Go nuts and run everything! Have fun!
If you have any questions about how any of the scripts work, please email me at [email protected] and I will get back to you as soon as I can. Have fun and good analysis!