Measuring memory is harder than you think: How to avoid problematic measurement practices in memory research

Author:

Brady Timothy F.ORCID,Robinson Maria MartinovnaORCID,Williams Jamal Rodgers,Wixted John

Abstract

We argue there is a ‘crisis of measurement’ in critical areas of memory research and provide concrete suggestions to improve the situation. In particular, we highlight the prevalence of memory studies that use tasks (like the “old/new” task: “have you seen this item before? yes/no”) where quantifying performance is deeply dependent on counterfactual reasoning that depends on the (unknowable) distribution of underlying memory signals. As a result of this difficulty, different literatures in memory research (e.g., visual working memory, eyewitness identification, picture memory, etc) have settled on a variety of fundamentally different metrics to get performance measures from such tasks (e.g., A’, corrected hit rate, percent correct, d’, diagnosticity ratios, K values, etc.), even though these metrics make different, contradictory assumptions about the distribution of latent memory signals, and even though all of their assumptions are frequently incorrect. We suggest that in order for the psychology and neuroscience of memory to become a more cumulative, theory-driven science, more attention must be given to measurement issues. We make a concrete suggestion: the default memory task for those simply interested in performance should change from old/new (“did you see this item’?”) to forced-choice (“which of these two items did you see?”). In situations where old/new variants are preferred (e.g., eyewitness identification; theoretical investigations of the nature of memory signals), receiver operating characteristic (ROC) analysis should always be performed rather than a binary old/new task.

Publisher

Center for Open Science

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3