Validating (easy) measures to combine speed and accuracy

实验心理学研究的主要部分产生了两种表现指标：按下两个按钮之一的速度（平均反应时间，平均RTs）和准确性（正确率百分比，PC）。这两种相互依赖的措施中，哪一种最相关，因此应纳入统计分析，以及将各自的其他措施视为附带措施是否安全，这些问题并不总是很清楚。问题是，在普通RTs和pc之间存在一种强烈的非任意关系，即速度的提高通常伴随着准确性的降低。综合措施旨在控制这种速度-精度权衡（SAT），以反映“真实”的性能。过去已经提出了几种结合这两个性能方面的措施，并在研究中大量使用。本项目旨在测试其有效性和范围。这将通过使用已建立的计算决策模型和目的收集的经验数据进行大规模模拟，并对性能和SAT水平进行实验操作。目的是确定（并进一步发展）那些有效控制sat和最好地反映2AFC任务的整体表现的措施，从而为未来关于依赖措施选择的实验心理学研究提供指导。一个潜在的结果是，所审查的措施都没有证明适合于这一目的。WP 1将重点关注用漂移扩散模型模拟的数据在参与者内的两两比较（因为参与者之间的设计被我们已经发表的研究所覆盖）。WP 2将使用各种模型和模型版本，这些模型和模型版本实现了用于生成sat的各种机制，以检查我们的结论是否可以推广到其他数据生成算法。WP 3将开发实验方法，以经验方式诱导期望的sat水平，并产生大规模的基准数据集。WP 4将仔细研究早期WP中出现的问题，并尝试解决这些问题。如果适用，WP 4还将进一步开发任何有前途的综合性能衡量标准。

The major share of experimental psychological studies produces two performance measures: the speed (mean response times, mean RTs) and accuracy (percentage correct, PC) of pressing one of two buttons (two-alternative forced choice tasks, 2AFC). It is not always clear, which of the two dependent measures is most relevant and should therefore be entered into statistical analyses and whether it is safe to treat the respective other measure as incidental. Problematically, there exists a strong, non-arbitrary relationship between mean RTs and PCs in that increasing speed usually comes with a corresponding decrease in accuracy. Combined measures aim to control for this speed-accuracy tradeoff (SAT), in order to reflect “true” performance. Several measures that combine both performance aspects have been suggested in the past and are heavily used in research. The present project aims to test their validity and scope. This will be done via large-scale simulations using established computational decision models and purpose-collected empirical data with experimental manipulations of performance and SAT levels. The aim is to identify (and further develop) those measures that effectively control for SATs and best reflect overall performance on 2AFC tasks and thereby to provide guidance for future experimental psychological studies with regard to the choice of dependent measures. One potential outcome is that none of the examined measures proofs suitable for this purpose. WP 1 will focus on pairwise within-participants comparisons on data simulated with the drift-diffusion model (because between-participants designs were covered by our already published study). WP 2 will use various models and model versions that implement various mechanisms that have been suggested to produce SATs to examine whether our conclusions generalize to other data-producing algorithms. WP 3 will develop experimental approaches to induced desired levels of SATs empirically and produce a large-scale benchmark data set. WP 4 will take a closer look on difficulties that have emerged in earlier WPs and try to resolve these. If applicable, WP 4 will also further develop any promising combined performance measures.