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The Factor Structure of Cognitive Functioning in Cognitively Healthy Participants: a Meta-Analysis and Meta-Analysis of Individual Participant Data.
Neuropsychology Review ( IF 5.8 ) Pub Date : 2020-02-01 , DOI: 10.1007/s11065-019-09423-6
Joost A Agelink van Rentergem 1, 2 , Nathalie R de Vent 1 , Ben A Schmand 1, 3, 4 , Jaap M J Murre 1 , Janneke P C Staaks 5 , , Hilde M Huizenga 1, 4, 6
Affiliation  

Many neuropsychologists are of the opinion that the multitude of cognitive tests may be grouped into a much smaller number of cognitive domains. However, there is little consensus on how many domains exist, what these domains are, nor on which cognitive tests belong to which domain. This incertitude can be solved by factor analysis, provided that the analysis includes a broad range of cognitive tests that have been administered to a very large number of people. In this article, two such factor analyses were performed, each combining multiple studies. However, because it was not possible to obtain complete multivariate data on more than the most common test variables in the field, not all possible domains were examined here. The first analysis was a factor meta-analysis of correlation matrices combining data of 60,398 healthy participants from 52 studies. Several models from the literature were fitted, of which a version based on the Cattell-Horn-Carroll (CHC) model was found to describe the correlations better than the others. The second analysis was a factor analysis of the Advanced Neuropsychological Diagnostics Infrastructure (ANDI) database, combining scores of 11,881 participants from 54 Dutch and Belgian studies not included in the first meta-analysis. Again, the model fit was better for the CHC model than for other models. Therefore, we conclude that the CHC model best characterizes both cognitive domains and which test belongs to each domain. Therefore, although originally developed in the intelligence literature, the CHC model deserves more attention in neuropsychology.

中文翻译:

认知健康参与者认知功能的因素结构:荟萃分析和个体参与者数据的荟萃分析。

许多神经心理学家认为,大量的认知测试可以分为数量少得多的认知领域。然而,对于存在多少个领域、这些领域是什么,以及哪些认知测试属于哪个领域,几乎没有达成共识。这种不确定性可以通过因素分析来解决,前提是该分析包括对大量人员进行的广泛的认知测试。在本文中,进行了两次此类因素分析,每次分析都结合了多项研究。然而,由于不可能获得超过该领域最常见测试变量的完整多变量数据,因此此处并未检查所有可能的领域。第一项分析是相关矩阵的因子荟萃分析,结合了来自 52 项研究的 60,398 名健康参与者的数据。拟合了文献中的多个模型,其中基于 Cattell-Horn-Carroll (CHC) 模型的版本比其他模型更能描述相关性。第二项分析是对高级神经心理学诊断基础设施 (ANDI) 数据库进行的因子分析,综合了来自 54 项荷兰和比利时研究(未包含在第一项荟萃分析中)的 11,881 名参与者的分数。同样,CHC 模型的模型拟合效果优于其他模型。因此,我们得出结论,CHC 模型最好地表征了两个认知领域以及哪个测试属于每个领域。因此,尽管 CHC 模型最初是在智力文献中开发的,但它在神经心理学中值得更多的关注。
更新日期:2020-02-01
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