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A Bayesian Rate Ratio Effect Size to Quantify Intervention Effects for Count Data in Single Case Experimental Research
This article formulates a within-subject Bayesian rate ratio effect size (BRR) for autocorrelated count data that would obviate the need for small sample corrections. The authors illustrate this within-subject effect size using real data for an ABAB design and provide codes for practitioners who may want to compute BRR.
Date:
June 19, 2020
Creator:
Batley, Pathiba Natesan; Mehta, Smita S. & Hitchcock, John H.
System:
The UNT Digital Library