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gmoTree – Get and Modify oTree Data

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

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 oTree list.

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 oTree list. 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 oTree list. 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 constant variables.
• 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

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.