This article describes the use of statistical significance tests and distance-based effect sizes with behavioral data from single case experimental designs (SCEDs). Such data often are interpreted only with visual analysis. However, a growing movement in the field is to quantify results to improve decision-making and communication across studies and sciences. The goal of the present study was to assess the agreement between visual analysis and various statistical tests. We recruited visual analysts to judge 160 pairwise data sets from published articles and compared these analyses to significance tests and effect sizes. One-tailed significance testing of Tau z and the percentage of pairwise differences in the predicted direction (PWD) generally agreed with each other, and complemented the effect sizes of Ratio of Distances (RD) and g. Visual analysis was somewhat unreliable and should be combined with statistical complements to maximize decision accuracy.

中文翻译：

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用效应大小和统计显着性检验对行为数据进行量化

本文描述了统计显着性检验和基于距离的效应大小与来自单案例实验设计 (SCED) 的行为数据的使用。此类数据通常只能通过视觉分析来解释。然而，该领域越来越多的运动是量化结果，以改善跨研究和科学的决策制定和交流。本研究的目的是评估视觉分析和各种统计测试之间的一致性。我们招募了视觉分析师来判断已发表文章中的 160 个成对数据集，并将这些分析与显着性检验和效应量进行比较。Tau z 的单尾显着性检验和预测方向 (PWD) 的成对差异百分比基本一致，并补充了距离比 (RD) 和克。视觉分析有些不可靠，应结合统计补充以最大限度地提高决策准确性。