Compare adaptive interventions in a SMART with a continuous, longitudinal outcome (linear mixed modeling)

About This Code

This code is used to estimate and compare the mean change in a longitudinal outcome for the adaptive interventions embedded in a SMART using a marginal linear mixed modeling approach.

How can a behavioral scientist use this code?

Behavioral intervention scientists can use this code to make inferences about the relative causal effects of one adaptive intevention versus another using data from a SMART with a longitudinal outcome.

What method does this code implement?

This code implements a pseudo maximum likelihood estimation (MLE) approach. A pseudo MLE is necessary because we are targeting a marginal likelihood (as opposed to targeting the likelihood that gave rise to the data); and therefore weights are used to define the likelihood function. In a SMART, the weights (which are potentially impacted by treatment) are known, by design.

Upcoming Events

Innovations in Methods for Adapting and Personalizing Interventions for Cancer Control

Saturday April 15, 2023 | 10:00 a.m. -11:30 a.m.
Annual Meeting of the Education Committee of the AACR
Learn More

Self-Relevant Appeals to Engage in Self-Monitoring of Alcohol Use: A Micro-randomized Trial

Friday April 28, 2023 | 1:00 p.m. MT
44th Annual Meeting & Scientific Sessions of the Society of Behavioral Medicine
Learn More

The Hybrid Experimental Design

Friday April 28, 2023 | 1:00 p.m. MT
44th Annual Meeting & Scientific Sessions of the Society of Behavioral Medicine
Learn More

Time-Varying Model of Engagement with Digital Self Reporting

Friday April 28, 2023 | 1:00pm MT
44th Annual Meeting & Scientific Sessions of the Society of Behavioral Medicine
Learn More

Results of the Sense2Stop Micro-Randomized Trial

Friday April 28, 2023 | 11:00 a.m. MT
44th Annual Meeting & Scientific Sessions of the Society of Behavioral Medicine
Learn More

LET’S STAY IN TOUCH

Join the d3center Mailing List

Keep up to date with the latest news, events, software releases, learning modules, and resources from the d3center.