Combining Nonoverlap and Trend for Single-Case Research: Tau-U
Combining Nonoverlap and Trend for Single-Case Research: Tau-U
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DOI：
10.1016/j.beth.2010.08.006
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发表时间：
2011-06-01
期刊：
影响因子：
3.7
通讯作者：
Sauber, Stephanie B.
中科院分区：
文献类型：
--
作者：
Parker, Richard I.;Vannest, Kimberly J.;Sauber, Stephanie B.
提出了一个新的单例研究数据的分析指标，Tau-U，它结合了阶段之间的不重叠与干预阶段内的趋势。此外，它还提供了控制不良A相趋势的选项。Tau-U的推导从肯德尔的秩相关和组间的Mann-Whitney U检验证明。趋势和非重叠的等价性也显示出来，从外地领导人的支持性引文。Tau-U计算证明了简单的AB和阿坝设计。然后，Tau-U在382个已公布的数据系列的样本上进行现场测试。控制不期望的A相趋势仅引起非重叠的适度变化。纳入B期趋势产生的结果比简单的非重叠更温和。Tau-U分数分布没有显示所有其他非重叠技术所显示的人为上限。它对自相关数据的表现相当不错。Tau-U显示了单例应用的前景，但需要进一步研究。
A new index for analysis of single-case research data was proposed, Tau-U, which combines nonoverlap between phases with trend from within the intervention phase. In addition, it provides the option of controlling undesirable Phase A trend. The derivation of Tau-U from Kendall's Rank Correlation and the Mann-Whitney U test between groups is demonstrated. The equivalence of trend and nonoverlap is also shown, with supportive citations from field leaders. Tau-U calculations are demonstrated for simple AB and ABA designs. Tau-U is then field tested on a sample of 382 published data series. Controlling undesirable Phase A trend caused only a modest change from nonoverlap. The inclusion of Phase B trend yielded more modest results than simple nonoverlap. The Tau-U score distribution did not show the artificial ceiling shown by all other nonoverlap techniques. It performed reasonably well with autocorrelated data. Tau-U shows promise for single-case applications, but further study is desirable.