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.
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