https://github.com/zauchnerp/gmotree
gmoTree is an R package developed for importing, merging, and efficiently managing oTree data.
https://github.com/zauchnerp/gmotree
otree r rpackage
Last synced: 8 months ago
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gmoTree is an R package developed for importing, merging, and efficiently managing oTree data.
- Host: GitHub
- URL: https://github.com/zauchnerp/gmotree
- Owner: ZauchnerP
- Created: 2023-08-24T18:44:32.000Z (almost 3 years ago)
- Default Branch: master
- Last Pushed: 2024-12-07T14:06:52.000Z (over 1 year ago)
- Last Synced: 2025-01-11T22:20:15.112Z (over 1 year ago)
- Topics: otree, r, rpackage
- Language: R
- Homepage: https://zauchnerp.github.io/gmoTree/
- Size: 4.3 MB
- Stars: 4
- Watchers: 2
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# gmoTree – Get and Modify oTree Data
[](https://cran.r-project.org/package=gmoTree)
[](https://github.com/ZauchnerP/gmoTree/actions/workflows/R-CMD-check.yaml)
[](https://r-pkg.org/pkg/gmoTree)
gmoTree is an R package developed for importing, merging, and
efficiently managing data obtained from running
oTree (Chen et al., 2016) experiments.
It’s particularly valuable when dealing with complex experimental
designs that span multiple sessions and generate a large number of files
that need to be integrated.[^1]
[^1]: gmoTree is not an official package of the oTree team but is built to complement the oTree open-source platform.
# Installation
To install the CRAN version of this package, use the following command:
`install.packages("gmoTree")`
To install the development version:
`devtools::install_github("ZauchnerP/gmoTree")`
# List of all functions
See the page
Introduction
to gmoTree for a more detailed overview of most of the functions.
For further details on the package as a whole, visit the
gmoTree website.
## Importing data
- `import_otree()`: Imports your oTree data and combines them in a list of data frames.
## Cleaning up data
- `messy_chat()`: Checks for a messy `Chats` data frame and combines variables that refer to
the same concept.
- `messy_chat()`: Checks for a messy `Time` data frame and combines variables that refer to
the same concept.
- `delete_duplicate()`: Deletes duplicate rows from all data frames
in the list of data frames.
## Dealing with dropouts and deleting cases
- `show_dropouts()`: Shows participant codes of people who did not finish at (a) certain
app(s) or page(s).
- `delete_dropouts()`: Deletes the data of participants who did not finish at (a) certain
app(s) or page(s). This function deletes the participants’ data from all
data frames in the list of data frames. Caution: It does not delete the cases
from the original CSV and Excel files!
- `delete_cases()`: Deletes the data of specified participants from all data frames in the list of data frames. Caution: This function does not delete the data from the
original CSV and Excel files!
- `delete_sessions()`: Deletes the data of specified sessions from all data frames in the oTree
list. Caution: This function does not delete the data from the original
CSV and Excel files!
## Deleting sensitive information
- `delete_plabels()`: Deletes the variable `participant.label` from every app because it might
contain identifiable information on the participants, such as their
MTurk ID. Caution: This function does not delete the variable from the
original CSV and Excel files!
## Making IDs
- `make_ids()`: Makes participant, group, and session IDs that are the same across all
apps.
## Measuring time
- `apptime()`: Calculates the time spent on a specific app.
- `extime()`: Calculates the time spent on the experiment.
- `pagesec()`: Calculates the time spent on each page.
## Transferring variables between the apps
- `assignv()`: Copies a variable from the `all_apps_wide` data frame to the data frames
of all other apps.
- `assignv_to_aaw()`: Copies a variable from one of your data frames to the `all_apps_wide` data
frame.
## Before running the experiment
- `show_constant()`: Shows variables with no variation.
- `codebook()`: Creates a codebook based on the oTree code. See also the vignette gmoTree Codebooks.
# References
Chen, D. L., Schonger, M., & Wickens, C. (2016). oTree—An open-source platform for laboratory, online, and field experiments. Journal of Behavioral and Experimental Finance, 9, 88–97. https://doi.org/10.1016/j.jbef.2015.12.001