School of Psychology, University of Nottingham, University Park, Nottingham, NG7 2RD, UK.
Institute of Psychology, Otto von Guericke University Magdeburg, Magdeburg, Germany.
Behav Res Methods. 2022 Jun;54(3):1416-1427. doi: 10.3758/s13428-021-01673-8. Epub 2021 Oct 28.
We typically slow down after committing an error, an effect termed post-error slowing (PES). Traditionally, PES has been calculated by subtracting post-correct from post-error RTs. Dutilh et al. (Journal of Mathematical Psychology, 56(3), 208-216, 2012), however, showed PES values calculated in this way are potentially biased. Therefore, they proposed to compute robust PES scores by subtracting pre-error RTs from post-error RTs. Based on data from a large-scale study using the flanker task, we show that both traditional and robust PES estimates can be biased. The source of the bias are differential imbalances in the percentage of congruent vs. incongruent post-correct, pre-error, and post-error trials. Specifically, we found that post-correct, pre-error, and post-error trials were more likely to be congruent than incongruent, with the size of the imbalance depending on the trial type as well as the length of the response-stimulus interval (RSI). In our study, for trials preceded by a 700-ms RSI, the percentages of congruent trials were 62% for post-correct trials, 66% for pre-error trials, and 56% for post-error trials. Relative to unbiased estimates, these imbalances inflated traditional PES estimates by 37% (9 ms) and robust PES estimates by 42% (16 ms) when individual-participant means were calculated. When individual-participant medians were calculated, the biases were even more pronounced (40% and 50% inflation, respectively). To obtain unbiased PES scores for interference tasks, we propose to compute unweighted individual-participant means by initially calculating mean RTs for congruent and incongruent trials separately, before averaging congruent and incongruent mean RTs to calculate means for post-correct, pre-error and post-error trials.
我们通常在犯错后会放慢速度,这种现象被称为错误后减速(PES)。传统上,PES 是通过从错误后 RT 中减去正确后 RT 来计算的。然而,Dutilh 等人(《心理数学杂志》,第 56 卷,第 3 期,208-216 页,2012 年)表明,以这种方式计算的 PES 值可能存在偏差。因此,他们建议通过从错误后 RT 中减去预错误 RT 来计算稳健的 PES 得分。基于使用侧翼任务的大规模研究的数据,我们表明传统和稳健的 PES 估计都可能存在偏差。偏差的来源是一致的和不一致的正确后、预错误和错误后试验的百分比差异。具体来说,我们发现,与不一致的试验相比,正确后、预错误和错误后试验更有可能是一致的,不平衡的大小取决于试验类型以及反应刺激间隔(RSI)的长度。在我们的研究中,对于 700 毫秒 RSI 前的试验,一致试验的百分比分别为正确后试验的 62%、预错误试验的 66%和错误后试验的 56%。与无偏估计相比,当计算个体参与者平均值时,这些不平衡使传统 PES 估计值膨胀了 37%(9 毫秒),稳健 PES 估计值膨胀了 42%(16 毫秒)。当计算个体参与者中位数时,偏差甚至更为明显(分别膨胀 40%和 50%)。为了获得干扰任务的无偏 PES 得分,我们建议通过最初分别计算一致和不一致试验的平均 RT,然后平均一致和不一致的平均 RT 来计算正确后、预错误和错误后试验的平均值,从而计算无加权的个体参与者平均值。