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.

Access Links

View Code on GitHub

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Prevention Science and Methodology Group Virtual Grand Rounds
January 24, 2023
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Introduction to MAISYs

University of Florida Health Outcomes and Biomedical Informatics Grand Rounds
February 13, 2023
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Comprehensive Program for Adaptive Interventions Training in Education (CATIE)
March 14, 2023
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