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Correspondence between Fail-Safe k and Dual-Criteria Methods: Analysis of Data Series Stability
John Michael Falligant1, Michael P Kranak1, Jonathan D Schmidt1
1Kennedy Krieger Institute & Johns Hopkins University School of Medicine, 707 North Broadway, Baltimore, MD 21205 USA.
Abstract:
Barnard-Brak, Richman, Little, and Yang (Behaviour Research and Therapy, 102, 8-15, 2018) developed a structured-criteria metric, fail-safe k, which quantifies the stability of data series within single-case experimental designs (SCEDs) using published baseline and treatment data. Fail-safe k suggests the optimal point in time to change phases (e.g., move from Phase B to Phase C, reverse back to Phase A). However, this tool has not been tested with clinical data obtained in the course of care. Thus, the purpose of the current study was to replicate the procedures described by Barnard-Brak et al. with clinical data. We also evaluated the correspondence between the fail-safe k metric with outcomes obtained via dual-criteria and conservative-dual criteria methods, which are empirically supported methods for evaluating data-series trends within SCEDs. Our results provide some degree of support for use of this approach as a research tool with clinical data, in particular when evaluating small or medium treatment effect sizes, but further research is needed before this can be used widely by practitioners.
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