Effects of serial dependency on the agreement between visual and statistical inference.
Effects of serial dependency on the agreement between visual and statistical inference.
复制标题
序列依赖性对视觉和统计推断之间一致性的影响。
DOI：
10.1901/jaba.1978.11-277
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发表时间：
1978
影响因子：
2.9
通讯作者：
R. S. Vaught
中科院分区：
文献类型：
--
作者：
R. R. Jones;M. Weinrott;R. S. Vaught
行为数据的视觉和时间序列推论之间的比较表明，分数上的连续依赖可能会扰乱两种分析方法之间的一致性。如果研究人员遵循早先的建议，即使用时间序列分析来补充或确认视觉分析，那么这项研究的发现表明，当数据包含高水平的自相关性时，以及当时间序列分析表明可靠的行为变化时，这两种方法最常不一致。
Comparisons between visual and time-series inferences from behavioral data show that serial dependency in scores is likely to disrupt agreement between the two methods of analysis. If researchers follow an earlier recommendation that time-series analysis be used to supplement or confirm visual analysis, this study's findings suggest that the two methods will disagree most often when the data contain high levels of autocorrelation and when reliable behavorial changes are indicated by time-series analysis.