Journal
CONTEMPORARY CLINICAL TRIALS
Volume 85, Issue -, Pages -Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.cct.2019.105830
Keywords
Adaptive intervention; Gate-keeping approach; Omnibus test; Sample size calculation; Sequential multiple assignment randomized trial
Funding
- NIH R01 grant [MH109496]
- NIH R21 grant [MH108999]
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This article proposes a method to overcome limitations in current methods that address multiple comparisons of adaptive interventions embedded in sequential multiple assignment randomized trial (SMART) designs. Because a SMART typically consists of numerous adaptive interventions, inferential procedures based on pairwise comparisons of all may suffer a substantial loss in power after accounting for multiplicity. Meanwhile, traditional methods for multiplicity adjustments in comparing non-adaptive interventions require prior knowledge of correlation structures, which can be difficult to postulate when analyzing SMART data of adaptive interventions. To address the multiplicity issue, we propose a likelihood-based omnibus test that compares all adaptive interventions simultaneously, and apply it as a gate-keeping test for further decision making. Specifically, we consider a selection procedure that selects the adaptive intervention with the best observed outcome only when the proposed omnibus test reaches a pre-specified significance level, so as to control false positive selection. We derive the asymptotic distribution of the test statistic on which a sample size formula is based. Our simulation study confirms that the asymptotic approximation is accurate with a moderate sample size, and shows that the proposed test outperforms existing multiple comparison procedures in terms of statistical power. The simulation results also suggest that our selection procedure achieves a high probability of selecting a superior adaptive intervention. The application of the proposed method is illustrated with a real dataset from a depression management study.
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