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老化和认知中的转化反应时成本与加工模型之间的映射关系。

The mapping between transformed reaction time costs and models of processing in aging and cognition.

机构信息

School of Psychology.

出版信息

Psychol Aging. 2018 Nov;33(7):1093-1104. doi: 10.1037/pag0000298. Epub 2018 Oct 8.

DOI:10.1037/pag0000298
PMID:30299155
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6233521/
Abstract

Older adults tend to have slower response times (RTs) than younger adults on cognitive tasks. This makes the examination of domain-specific deficits in aging difficult, as differences between conditions in raw RTs (RT costs) typically increase with slower average RTs. Here, we examine the mapping between 2 established approaches to dealing with this confound in the literature. The first is to use transformed RT costs, with the z-score and proportional transforms both being commonly used. The second is to use mathematical models of choice RT behavior, such as the drift-diffusion model (Ratcliff, 1978). We simulated data for younger and older adults from the drift-diffusion model under 4 scenarios: (a) a domain specific deficit, (b) general slowing, (c) strategic slowing, and (d) a slowing of nondecision processes. In each scenario we varied the size of the difference between younger and older adults in the model parameters, and examined corresponding effect sizes and Type I error rates in the raw and transformed RT costs. The z-score transformation provided better control of Type I error rates than the raw or proportional costs, though did not fully control for differences in the general slowing and strategic slowing scenarios. We recommend that RT analyses are ideally supplemented by analyses of error rates where possible, as these may help to identify the presence of confounds. To facilitate this, it would be beneficial to include conditions that elicit below ceiling accuracy in tasks. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

摘要

老年人在认知任务上的反应时间(RT)往往比年轻人慢。这使得在衰老过程中检查特定领域的缺陷变得困难,因为在原始 RT(RT 成本)之间的条件差异通常随着平均 RT 的减慢而增加。在这里,我们研究了文献中处理这种混淆的两种已建立方法之间的映射。第一种是使用转换后的 RT 成本,其中 z 分数和比例转换都经常使用。第二种是使用选择 RT 行为的数学模型,如漂移扩散模型(Ratcliff,1978)。我们根据漂移扩散模型从年轻人和老年人模拟了 4 种情况的数据:(a)特定领域的缺陷,(b)普遍减速,(c)策略性减速,以及(d)非决策过程减速。在每种情况下,我们改变了模型参数中年轻人和老年人之间的差异大小,并检查了原始和转换后的 RT 成本中的相应效果大小和 I 型错误率。与原始或比例成本相比,z 分数转换提供了更好的 I 型错误率控制,但并未完全控制一般减速和策略性减速情况的差异。我们建议,在可能的情况下,最好对错误率进行 RT 分析的补充分析,因为这可能有助于识别混淆的存在。为了便于进行这种分析,在任务中引入引起低于上限准确性的条件将是有益的。(PsycINFO 数据库记录(c)2018 APA,保留所有权利)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c170/6233521/84b3cf402450/pag_33_7_1093_fig3a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c170/6233521/7e67ab8cb82d/pag_33_7_1093_fig1a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c170/6233521/f0854a59a957/pag_33_7_1093_fig2a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c170/6233521/84b3cf402450/pag_33_7_1093_fig3a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c170/6233521/7e67ab8cb82d/pag_33_7_1093_fig1a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c170/6233521/f0854a59a957/pag_33_7_1093_fig2a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c170/6233521/84b3cf402450/pag_33_7_1093_fig3a.jpg

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