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Assessing Consistency in Single-Case Data Features Using Modified Brinley Plots
Behavior Modification ( IF 2.0 ) Pub Date : 2020-12-28 , DOI: 10.1177/0145445520982969
Rumen Manolov 1 , René Tanious 2
Affiliation  

The current text deals with the assessment of consistency of data features from experimentally similar phases and consistency of effects in single-case experimental designs. Although consistency is frequently mentioned as a critical feature, few quantifications have been proposed so far: namely, under the acronyms CONDAP (consistency of data patterns in similar phases) and CONEFF (consistency of effects). Whereas CONDAP allows assessing the consistency of data patterns, the proposals made here focus on the consistency of data features such as level, trend, and variability, as represented by summary measures (mean, ordinary least squares slope, and standard deviation, respectively). The assessment of consistency of effect is also made in terms of these three data features, while also including the study of the consistency of an immediate effect (if expected). The summary measures are represented as points on a modified Brinley plot and their similarity is assessed via quantifications of distance. Both absolute and relative measures of consistency are proposed: the former expressed in the same measurement units as the outcome variable and the latter as a percentage. Illustrations with real data sets (multiple baseline, ABAB, and alternating treatments designs) show the wide applicability of the proposals. We developed a user-friendly website to offer both the graphical representations and the quantifications.



中文翻译:

使用修正的布林利图评估单一案例数据特征的一致性

目前的文本涉及评估来自实验相似阶段的数据特征的一致性以及单案例实验设计中的效果一致性。尽管一致性经常被提及为一个关键特征,但迄今为止很少有人提出量化:即在首字母缩略词下,CONDAP(相似阶段的数据模式的一致性)和 CONEFF(效果的一致性)。尽管 CONDAP 允许评估数据模式的一致性,但这里提出的建议侧重于数据特征的一致性,例如水平、趋势和可变性,由汇总度量(分别为平均值、普通最小二乘斜率和标准差)表示。效果一致性的评估也是根据这三个数据特征进行的,同时还包括研究即时效果的一致性(如果预期)。汇总度量表示为修改后的布林利图上的点,并且它们的相似性通过距离的量化来评估。提出了一致性的绝对和相对测量:前者以与结果变量相同的测量单位表示,后者以百分比表示。带有真实数据集(多基线、ABAB 和交替治疗设计)的插图显示了这些建议的广泛适用性。我们开发了一个用户友好的网站来提供图形表示和量化。提出了一致性的绝对和相对测量:前者以与结果变量相同的测量单位表示,后者以百分比表示。带有真实数据集(多基线、ABAB 和交替治疗设计)的插图显示了这些建议的广泛适用性。我们开发了一个用户友好的网站来提供图形表示和量化。提出了一致性的绝对和相对测量:前者以与结果变量相同的测量单位表示,后者以百分比表示。带有真实数据集(多基线、ABAB 和交替治疗设计)的插图显示了这些建议的广泛适用性。我们开发了一个用户友好的网站来提供图形表示和量化。

更新日期:2021-01-04
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