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Comparing network structures on three aspects: A permutation test.
Psychological Methods ( IF 10.929 ) Pub 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

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) 2022 APA, all rights reserved).

中文翻译:

在三个方面比较网络结构: 置换测试。

心理测量构造的网络方法,其中构造根据其组成因素之间的相互作用进行建模,在心理学中迅速普及。这种网络方法在各种心理结构中的应用最近已经从描述性立场(目标是估计与结构相关的网络结构)转变为更具比较性的立场,其中目标是比较人群中的网络结构. 但是,缺乏这样做的统计工具。在本文中,我们介绍了网络比较测试 (NCT),它使用基于重采样的置换测试来比较来自两个独立的横截面数据集的网络结构,了解 (a) 网络结构、(b) 边缘(连接)的不变性实力,以及 (c) 全球实力。在模拟中评估 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 类错误率接近标称显着性水平,如果样本量和网络之间的差异很大,则证明功效足够高。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 数据库记录 (c) 2022 APA,保留所有权利)。
更新日期:2022-04-11
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