One of our goals is to make the type of research we do as accessible as possible. In this section, you can access tutorials on how to conduct multi-level analyses on real-time monitoring (ecological momentary assessment, experience sampling) data. More tutorials will be added in the coming months!

Power Curves for Multi-level Studies

Any time that you are planning a study, it's a good idea to conduct power analyses to determine the appropriate sample size and sampling frequency. Power analyses for real-time data collection studies can be difficult because the tools to do so are not readily accessible. The purpose of this web app is to help estimate the needed sample size and sampling frequency to detect effects in multi-level studies (e.g., EMA/ESM and daily-diary) without needing to know any advanced programming languages.

R Packages

In this section, you can find information on the R packages we have developed for managing and analyzing data from real-time monitoring studies. We plan to update these tools regularly.

EMA Payment Estimator

You can use this tool to estimate the total cost of various compensation scenarios for studies that use EMA and other real-time monitoring technology (e.g., wearables).
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