Single-case experimental designs (SCED) evaluate treatment effects for each participant, but it is difficult to aggregate and quantify treatment effects across SCED participants receiving the same type of treatment. We applied Bayesian analytic procedures to SCED data aggregated across participants that have previously only been applied to large-N and group design studies of treatment effect sizes. For the current study, we defined transient elevated treatment data points as (1) above the range of the last five baseline sessions during the first three sessions of treatment (i.e., extinction burst); (2) within or above the range of baseline after the first three treatment sessions (i.e., recurrence burst); or (3) thinning phase data points above the last three prethinning treatment data points (i.e., thinning burst). Results indicated that the treatment effect sizes remained large regardless of controlling for transient elevated treatment data points. Finally, we examined the effects of reinforcer schedule thinning on estimates of treatment effect size. Results indicated a moderate negative impact of schedule thinning on treatment effect size with a 16% decrease in effect size. Recommendations for research and practice are provided, and the utility of using Bayesian analysis in single-case experimental designs is discussed.

中文翻译：

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治疗爆发数据点和单例设计研究：用于估计治疗效果大小的贝叶斯N-of-1分析。

单例实验设计（SCED）评估了每个参与者的治疗效果，但是很难对接受相同类型治疗的SCED参与者的治疗效果进行汇总和量化。我们将贝叶斯分析程序应用于参与者之间汇总的SCED数据，这些数据以前仅应用于大型N和小组设计研究治疗效果的大小。对于当前的研究，我们将短暂升高的治疗数据点定义为（1）在治疗的前三个疗程（即灭绝爆发）中高于最后五个基线疗程的范围；（2）在前三个治疗阶段（即复发爆发）后，在基线范围内或之上；或（3）在最后三个预稀疏处理数据点之上的稀疏阶段数据点（即稀疏突发）。结果表明，无论控制瞬时升高的治疗数据点如何，治疗效果的大小均保持较大。最后，我们检查了补强片减薄对治疗效果大小估计值的影响。结果表明，计划减薄对治疗效果大小有中等程度的负面影响，效果大小减少了16％。