Calculate the sample size for a SMART with a binary, longitudinal outcome, in which the primary aim is to compare the log-odds of success between two adaptive interventions

About This Code

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 success between two adaptive interventions starting with different interventions.

How can a behavioral scientist use this code?

Behavioral intervention scientists can use this code to calculate the sample size for SMART with a binary outcome.

What method does this code implement?

This code implements sample size formulae based on a test of the null hypothesis that the difference in probabilities of success between two adaptive interventions is zero.