About this code
This code is used to estimate and compare change in the log-odds of success in a binary longitudinal outcome for the adaptive interventions embedded in a SMART.
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 intervention versus another using data from a SMART with a longitudinal binary outcome.
What method does this code implement?
This code implements a weighted least squares regression approach that is similar to longitudinal regression analyses using GEE with a logit link. In a SMART, the weights (which are potentially impacted by treatment) are known, by design.
Related References
Dziak, J. J., Almirall, D., Dempsey, W., Stanger, C., & Nahum-Shani, I. (2024). SMART Binary: New Sample Size Planning Resources for SMART Studies with Binary Outcome Measurements. Multivariate Behavioral Research, 59(1), 1–16. doi:10.1080/00273171.2023.2229079
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