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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 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.

gmoTree is not an official package of the oTree team, but it was created to complement the open-source platform.

Installation

To install the CRAN version of this package, use the following command:

install.packages("gmoTree")

To install the development versions:

devtools::install_github("ZauchnerP/gmoTree")

List of all functions

See the page Introduction to gmoTree for a more detailed overview 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