Comparing network structures on three aspects: A permutation test.

IF 4.4 2区 化学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY ACS Applied Polymer Materials Pub Date : 2023-12-01 Epub Date: 2022-04-11 DOI:10.1037/met0000476
Claudia D van Borkulo, Riet van Bork, Lynn Boschloo, Jolanda J Kossakowski, Pia Tio, Robert A Schoevers, Denny Borsboom, Lourens J Waldorp
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引用次数: 417

Abstract

Network approaches to psychometric constructs, in which constructs are modeled in terms of interactions between their constituent factors, have rapidly gained popularity in psychology. Applications of such network approaches to various psychological constructs have recently moved from a descriptive stance, in which the goal is to estimate the network structure that pertains to a construct, to a more comparative stance, in which the goal is to compare network structures across populations. However, the statistical tools to do so are lacking. In this article, we present the network comparison test (NCT), which uses resampling-based permutation testing to compare network structures from two independent, cross-sectional data sets on invariance of (a) network structure, (b) edge (connection) strength, and (c) global strength. Performance of NCT is evaluated in simulations that show NCT to perform well in various circumstances for all three tests: The Type I error rate is close to the nominal significance level, and power proves sufficiently high if sample size and difference between networks are substantial. We illustrate NCT by comparing depression symptom networks of males and females. Possible extensions of NCT are discussed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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从三个方面比较网络结构:排列检验。
心理测量构念的网络方法是根据构念的组成因素之间的相互作用来建模的,这种方法在心理学中迅速流行起来。这种网络方法在各种心理构念中的应用,最近已经从描述性立场(其目标是估计与构念相关的网络结构)转变为更具比较性的立场(其目标是比较不同人群的网络结构)。然而,目前缺乏这样做的统计工具。在本文中,我们提出了网络比较测试(NCT),它使用基于重采样的排列测试来比较来自两个独立的横截面数据集的网络结构在(a)网络结构,(b)边缘(连接)强度和(c)全局强度的不变性。在模拟中评估了NCT的性能,显示NCT在所有三个测试的各种情况下都表现良好:I型错误率接近名义显著性水平,如果样本大小和网络之间的差异很大,则功率证明足够高。我们通过比较男性和女性的抑郁症状网络来说明NCT。讨论了NCT的可能扩展。(PsycInfo Database Record (c) 2022 APA,版权所有)。
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来源期刊
CiteScore
7.20
自引率
6.00%
发文量
810
期刊介绍: ACS Applied Polymer Materials is an interdisciplinary journal publishing original research covering all aspects of engineering, chemistry, physics, and biology relevant to applications of polymers. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrates fundamental knowledge in the areas of materials, engineering, physics, bioscience, polymer science and chemistry into important polymer applications. The journal is specifically interested in work that addresses relationships among structure, processing, morphology, chemistry, properties, and function as well as work that provide insights into mechanisms critical to the performance of the polymer for applications.
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