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Ep. 21- JABA in One Take- A unique example of machine learning to behavior analysis

show notes Dec 03, 2021

JABA in One Take- Show Notes

To end out the week, we have something truly out of left field. The application of machine learning to behavior analytic single case design graphs. These authors focus on the teeter totter between type 1 and type 2 errors. The less type 1 errors, the higher the probability that rater is susceptible to type 2 errors. This presents a particularly interesting challenge for our field, as we stray away from type 1 errors and accept more type 2 errors. This error bias is inherent in our visual analysis methods and our expectation of clear and strong demonstrations of effect size. Due to conflicting research related to the reliability of visual analysis, these authors attempt to demonstrate a potential solution.

Citation + DOI

Lanovaz, M. J., & Hranchuk, K. (2021). Machine learning to analyze single-case graphs: A comparison to visual inspection. Journal of Applied Behavior Analysis, 54(4), 1541-1552.

Additional Readings:

Lanovaz, M. J., Turgeon, S., Cardinal, P., & Wheatley, T. L. (2019). Using single-case designs in practical settings: Is replication always necessary? Perspectives on Behavior Science, 42, 153-162. https://doi. org/10.1007/s40614-018-0138-9

Fisher, W. W., Kelley, M. E., & Lomas, J. E. (2003). Visual aids and structured criteria for improving visual inspection and interpretation of single-case designs. Journal of Applied Behavior Analysis, 36(3), 387-406.

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