Oregon Research Institute.
J Appl Behav Anal. 1977 Spring;10(1):151-66. doi: 10.1901/jaba.1977.10-151.
A time-series method is presented, nontechnically, for analysis of data generated in individual-subject operant studies, and is recommended as a supplement to visual analysis of behavior change in reversal or multiple-baseline experiments. The method can be used to identify three kinds of statistically significant behavior change: (a) changes in score levels from one experimental phase to another, (b) reliable upward or downward trends in scores, and (c) changes in trends between phases. The detection of, and reliance on, serial dependency (autocorrelation among temporally adjacent scores) in individual-subject behavioral scores is emphasized. Examples of published data from the operant literature are used to illustrate the time-series method.
本文提出了一种时间序列方法，用于分析个体被试操作性研究中产生的数据，推荐作为逆转或多次基线实验中行为变化的视觉分析的补充。该方法可用于识别三种具有统计学意义的行为变化：（a）从一个实验阶段到另一个实验阶段得分水平的变化，（b）得分的可靠上升或下降趋势，以及（c）阶段之间趋势的变化。强调了在个体被试行为得分中检测和依赖序列相关性（时间上相邻得分之间的自相关）。使用操作性文献中发表的数据的示例来说明时间序列方法。
