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Estimating systematic and random sources of variability in perceptual decision-making: A reply to Evans, Tillman, & Wagenmakers (2020).

心理信息 随机效应模型 心理学 感知 荟萃分析 统计 计量经济学 认知心理学 数学 梅德林 医学 政治学 内科学 神经科学 法学
作者
Roger Ratcliff,Philip L. Smith
出处
期刊:Psychological Review [American Psychological Association]
卷期号:128 (5): 988-994 被引量:3
标识
DOI:10.1037/rev0000212
摘要

Ratcliff, Voskuilen, and McKoon (2018) presented data and model-based analyses that provided strong evidence for across-trial variability in evidence entering the decision process in several perceptual tasks. They did this using a double-pass procedure in which exactly the same stimuli are presented on two widely-separated trials. If there were only random variability (i.e., the first and second presentations of a stimulus were independent), then the agreement in the choice made on the two trials would be a function of accuracy: as accuracy increases from chance to 100% correct, then the probability of agreement increases. In the experiments, agreement was greater than that predicted from independence which means that there was systematic variability in items from trial to trial. Evans et al. (2020) criticized this by arguing that because of possible tradeoffs among parameters, the evidence did not support two sources of across-trial variability, but rather the results could be explained by only a systematic (item) component of variability. However, their own analysis showed that parameter estimates were accurate enough to support identification of the two sources of variability. We present a new analysis of possible sources of across-trial variability in evidence and show that systematic variability can be estimated from accuracy-agreement functions with a functional form that depends on only two diffusion model parameters. We also point out that size of the estimates of these two sources are model-dependent. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

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