This code calculates the minimum sample size necessary for a SMART with a binary longitudinal outcome, in which the primary aim is a comparison of the log-odds of sucess between two adaptive interventions starting with different interventions.
This code calculates the minimum sample size necessary for a SMART with a continuous longitudinal outcome, in which the primary aim is a comparison of the mean of the outcome between two adaptive interventions starting with different interventions.
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.
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.
This code is used to estimate and compare the mean change in a longitudinal outcome for the adaptive interventions embedded in a SMART.