About this code
This code is used to estimate the causal effect of a just-in-time intervention component on the mean of a continuous proximal or distal outcome using data from an MRT.
How can a behavioral scientist use this code?
Behavioral intervention scientists can use this code to make statistical inferences about the proximal and lagged causal effects of a JITAI intervention component on a continuous outcome. This code can also be used by behavioral intervention scientists to assess how the causal effect of a just-in-time intervention component is moderated by time-varying factors.
What method does this code implement?
This code implements an easy-to-use, weighted least squares regression estimator for assessing causal effects of just-in-time components in an MRT. In an MRT, the weights (which are potentially impacted by prior treatment) are known, by design.
Related References
Boruvka, A., Almirall, D., Witkiewitz, K., & Murphy, S. A. (2018). Assessing Time-Varying Causal Effect Moderation in Mobile Health. Journal of the American Statistical Association, 113(523), 1112–1121. https://doi.org/10.1080/01621459.2017.1305274