SMART longitudinal analysis: A tutorial for using repeated outcome measures from SMART studies to compare adaptive interventions

Inbal Nahum-Shani, Daniel Almirall, Jamie R.T. Yap, James R. McKay, Kevin G. Lynch, Elizabeth A. Freiheit, John J. Dziak

    Research output: Contribution to journalArticlepeer-review

    27 Scopus citations


    In recent years, there has been increased interest in the development of adaptive interventions across various domains of health and psychological research. An adaptive intervention is a protocolized sequence of individualized treatments that seeks to address the unique and changing needs of individuals as they progress through an intervention program. The sequential, multiple assignment, randomized trial (SMART) is an experimental study design that can be used to build the empirical basis for the construction of effective adaptive interventions. A SMART involves multiple stages of randomizations; each stage of randomization is designed to address scientific questions concerning the best intervention option to employ at that point in the intervention. Several adaptive interventions are embedded in a SMART by design; many SMARTs are motivated by scientific questions that concern the comparison of these embedded adaptive interventions. Until recently, analysis methods available for the comparison of adaptive interventions were limited to end-of-study outcomes. The current article provides an accessible and comprehensive tutorial to a new methodology for using repeated outcome data from SMART studies to compare adaptive interventions. We discuss how existing methods for comparing adaptive interventions in terms of end-of-study outcome data from a SMART can be extended for use with longitudinal outcome data. We also highlight the scientific utility of using longitudinal data from a SMART to compare adaptive interventions. A SMART study aiming to develop an adaptive intervention to engage alcohol- and cocaine-dependent individuals in treatment is used to demonstrate the application of this new methodology.

    Original languageEnglish (US)
    Pages (from-to)1-29
    Number of pages29
    JournalPsychological Methods
    Issue number1
    StatePublished - Feb 1 2020

    All Science Journal Classification (ASJC) codes

    • Psychology (miscellaneous)


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