  A dynamic treatment regimen (DTR) is a pre-specified sequence of decision
rules which maps baseline or time-varying measurements on an individual to a
recommended intervention or set of interventions. Sequential multiple
assignment randomized trials (SMARTs) represent an important data collection
tool for informing the construction of effective DTRs. A common primary aim in
a SMART is the marginal mean comparison between two or more of the DTRs
embedded in the trial. This manuscript develops a mixed effects modeling and
estimation approach for these primary aim comparisons based on a continuous,
longitudinal outcome. The method is illustrated using data from a SMART in
autism research.
