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. 2021 Apr;54(2):824-833.
doi: 10.1002/jaba.789. Epub 2020 Oct 20.

Application of automated nonparametric statistical analysis in clinical contexts

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Application of automated nonparametric statistical analysis in clinical contexts

Michael P Kranak et al. J Appl Behav Anal. 2021 Apr.

Abstract

Functional analyses (FAs) provide clinicians with results upon which they design behavioral treatments. Unfortunately, interrater reliability of visual analysis of FA results can be inconsistent. Accordingly, researchers have designed quantitative metrics and visual aids to supplement visual analysis. Recently, Hall et al. (2020) provided a proof of concept for using automated nonparametric statistical analysis (ANSA) to interpret FA data. Their results show promise for ANSA as a supplemental tool. However, they evaluated ANSA with only published FA datasets, which may not be representative of FAs commonly encountered in clinical care. Therefore, the purpose of this replication was to compare ANSA to another validated supplemental aid (i.e., the structured criteria method) and investigate its utility with unpublished clinical FA data. Our results were consistent with Hall et al.'s, indicating ANSA may augment clinical interpretation of FA data. Recommendations for clinical applications of ANSA and future directions for researchers are discussed.

Keywords: data interpretation; functional analysis; statistical analysis; structured criteria; visual analysis.

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REFERENCES

    1. Abdi, H. (2007). Binomial distribution: Binomial and sign tests. In N. Salkind (Ed.), Encyclopedia of measurement and statistics (pp. 1-5). Thousand Oaks.
    1. Barnard-Brak, L., Richman, D. M., Little, T. D., & Yang, Z. (2018). Development of an in-vivo metric to aid visual inspection of single-case design data: Do we need to run more sessions? Behavior Research and Therapy, 102, 8-15. https://doi.org/10.1016/j.brat.2017.12.003
    1. Betz, A. M., & Fisher, W. W. (2011). Functional analysis: History and methods. In W. W. Fisher, C. C. Piazza, & H. S. Roane (Eds.). Handbook of applied behavior analysis (pp. 206-225). Guilford.
    1. Branch, M. N., & Pennypacker, H. S. (2003). Generality and generalization of research findings. In G. J. Madden, W. V. Dube, T. D. Hackenberg, G. P. Hanley, & K. A. Lattal (Eds.), APA handbook of behavior analysis, Vol. 1. Methods and principles (pp. 171-175). American Psychological Association. https://doi.org/10.1037/13937-007
    1. Craig, A. R., & Fisher, W. W. (2019). Randomization tests as alternative analysis methods for behavior-analytic data. Journal of the Experimental Analysis of Behavior, 111(2), 309-328. https://doi.org/10.1002/jeab.500

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