California State University San Bernardino, Palm Desert Campus, CSUSB-PDC, 37500 Cook Street, Palm Desert, CA, 92211, USA.
Universitat de València, Valencia, Spain.
Behav Res Methods. 2021 Feb;53(1):49-58. doi: 10.3758/s13428-020-01424-1.
Estimating the time course of the influence of different factors in human performance is one of the major topics of research in cognitive psychology/neuroscience. Over the past decades, researchers have proposed several methods to tackle this question using latency data. Here we examine a recently proposed procedure that employs survival analyses on latency data to provide precise estimates of the timing of the first discernible influence of a given factor (e.g., word frequency on lexical access) on performance (e.g., fixation durations or response times). A number of articles have used this method in recent years, and hence an exploration of its strengths and its potential weaknesses is in order. Unfortunately, our analysis revealed that the technique has conceptual flaws, and it might lead researchers into believing that they are obtaining a measurement of processing components when, in fact, they are obtaining an uninterpretable measurement.
估计不同因素对人类表现影响的时间进程是认知心理学/神经科学的主要研究课题之一。在过去几十年中，研究人员已经提出了几种使用潜伏期数据来解决这个问题的方法。在这里，我们研究了一种最近提出的程序，该程序使用生存分析对潜伏期数据进行分析，以提供给定因素（例如，词汇频率对词汇访问的影响）对表现（例如，注视持续时间或反应时间）的第一个可察觉影响的时间的精确估计。近年来，许多文章都使用了这种方法，因此，有必要对其优缺点进行探讨。不幸的是，我们的分析表明该技术存在概念上的缺陷，它可能会使研究人员误以为他们正在获得处理成分的测量值，而实际上他们正在获得无法解释的测量值。
