This example code calculates the minimum sample size for Sense2Stop, a 10-day, stratified micro-randomized trial. Study participants wear a chest and wrist band sensors that are used to construct a binary, time-varying stress classification at each minute of the day. The intervention is a smartphone notification to remind the participant to access a smartphone app and practice stress-reduction exercises. Intervention delivery is constrained to limit participant burden (a limit on the number of reminders sent) and to times at which the sensor-based stress classification is possible. The trial was designed to answer the questions: "Is there an effect of the reminder on near-term, proximal stress if the individual is currently experiencing stress? And, does the effect of the reminder vary with time in study?"
The code simulates and analyzes data from a hypothetical hybrid trial combining SMART and MRT features, in association with the manuscript "Hybrid Experimental Designs for Intervention Development: What, Why and How" by Nahum-Shani et al (2022).
The Substance Abuse Research Assistant (SARA) Micro-Randomized Trial: Workflow and templates for reproducing results
The Substance Abuse Research Assistance (SARA) Micro-Randomized Trial: Workflow and templates for reproducing results.
This example code describes the curation and analysis of data from a micro-randomized trial (MRT) among college students. The MRT was designed to estimate the effect of just in time digital prompts (reminders) on engagement in self-monitoring for alcohol use.
This example code describes the sample size and statistical power considerations in the design of the MARS Micro-Randomized Trial.