EMA-CleanR is a program for efficient pre-processing, cleaning, and visualization of Ecological Momentary Assessment (EMA) survey data in R to enable high-quality, real-time behavioral insights. It was created by Dr. Sarah Sperry and Victoria Murphy of the Emotion and Temporal Dynamics (EmoTe) Lab at the University of Michigan.
- To view sample data and a code walk-through, simply visit: https://depressioncenter.github.io/EMA-CleanR/EMA-CleanR.html
- To use with your own data, first download and extract this repository (or clone it).
- Replace EMA-Data.csv with your own file.
- Ensure it has at least these columns: participantidentifier,surveyname,start_datetime,end_datetime
- There should be one column per question, and the column headings should start with "EMA_" (e.g. EMA_01, EMA_02, etc.)
- Each row represents one survey taken by one participant at one point in time.
- Open EMA-CleanR.Rmd with R-Studio. If asked, install any missing packages.
- Edit the parameters at the top if needed (e.g. input file name), in the YAML section.
- Click the "Knit" button (or Ctrl+Shift+K) to generate a new EMA-CleanR.html file. This will contain a walk-through analysis of your data and visualizations.
- The output directory will contain exports of the data analysis in CSV format.
- The full documentation is available at: https://teamdynamix.umich.edu/TDClient/210/DepressionCenter/KB/ArticleDet?ID=14610
- EmoTe Lab projects - https://sperry.lab.medicine.umich.edu/active-projects
The Emotion and Temporal Dynamics (EmoTe) Lab, directed by Dr. Sarah Sperry, in the Department of Psychiatry at the University of Michigan and affiliated with the Heinz C. Prechter Bipolar Research Program, has a broad mission to improve early detection, predict illness trajectory, and develop personalized interventions for bipolar spectrum disorders (BSDs). Within this broader mission we are working to better characterize and understand intraindividual variability in emotion and behavior in real-world contexts. We use digital phenotyping methods (smartphones and wearables) and advanced idiographic statistical methods to model dynamics over both micro (e.g., momentary) and macro (e.g., years) timescales.
Learn more at: EmoTe Lab
The code for this project is maintained in collaboration with the Eisenberg Family Depression Center (@DepressionCenter) at the University of Michigan.
To get in touch, contact the individual developers in the check-in history.
If you need assistance identifying a contact person, email the project maintainers at: efdc-mobiletech@umich.edu.
- Sarah Sperry
- Victoria Murphy (@victoria-murphy)
- Gabriel Mongefranco (@gabrielmongefranco)
- Eisenberg Family Depression Center (@DepressionCenter)
- Emotion-based Impulsivity in Bipolar Disorder (EBI-BD) study
- EFDC TDX Knowldge Base Templates
- R libraries used: dplyr, psych, tidyverse, lubridate, table1, corrplot, ggplot2, patchwork, rlang
Copyright © 2025 The Regents of the University of Michigan
This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this program. If not, see https://www.gnu.org/licenses/gpl-3.0-standalone.html.
Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.3 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. You should have received a copy of the license included in the section entitled "GNU Free Documentation License". If not, see https://www.gnu.org/licenses/fdl-1.3-standalone.html
If you find this repository, code or paper useful for your research, please cite it.
Sperry, Sarah; Murphy, Victoria (2025). EMA-CleanR. University of Michigan. Software. https://github.com/DepressionCenter/EMA-CleanR
DOI: 10.5281/zenodo.17982076
Copyright © 2025 The Regents of the University of Michigan