Department of Psychology, University of Bern.
Department of Psychology, University of Neuchatel.
Psychol Methods. 2024 Apr;29(2):421-433. doi: 10.1037/met0000499. Epub 2022 Jun 23.
Cross-lagged models are by far the most commonly used method to test the prospective effect of one construct on another, yet there are no guidelines for interpreting the size of cross-lagged effects. This research aims to establish empirical benchmarks for cross-lagged effects, focusing on the cross-lagged panel model (CLPM) and the random intercept cross-lagged panel model (RI-CLPM). We drew a quasirepresentative sample of studies published in four subfields of psychology (i.e., developmental, social-personality, clinical, and industrial-organizational). The dataset included 1,028 effect sizes for the CLPM and 302 effect sizes for the RI-CLPM, based on data from 174 samples. For the CLPM, the 25th, 50th, and 75th percentiles of the distribution corresponded to cross-lagged effect sizes of .03, .07, and .12, respectively. For the RI-CLPM, the corresponding values were .02, .05, and .11. Effect sizes did not differ significantly between the CLPM and RI-CLPM. Moreover, effect sizes did not differ significantly across subfields and were not moderated by design characteristics. However, effect sizes were moderated by the concurrent correlation between the constructs and the stability of the predictor. Based on the findings, we propose to use .03 (small effect), .07 (medium effect), and .12 (large effect) as benchmark values when interpreting the size of cross-lagged effects, for both the CLPM and RI-CLPM. In addition to aiding in the interpretation of results, the present findings will help researchers plan studies by providing information needed to conduct power analyses and estimate minimally required sample sizes. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
交叉滞后模型是迄今为止最常用于测试一个结构对另一个结构的前瞻性影响的方法，但目前还没有解释交叉滞后效应大小的指南。本研究旨在为交叉滞后效应建立经验基准，重点关注交叉滞后面板模型（CLPM）和随机截距交叉滞后面板模型（RI-CLPM）。我们从发展心理学、社会人格心理学、临床心理学和工业组织心理学四个子领域发表的研究中抽取了一个准代表性样本。该数据集包括 174 个样本的 1028 个 CLPM 效应大小和 302 个 RI-CLPM 效应大小。对于 CLPM，分布的 25%、50%和 75%分位数对应的交叉滞后效应大小分别为.03、.07 和.12。对于 RI-CLPM，相应的值为.02、.05 和.11。CLPM 和 RI-CLPM 之间的效应大小没有显著差异。此外，效应大小在子领域之间没有显著差异，也不受设计特征的调节。然而，效应大小受到结构之间的同期相关性和预测器的稳定性的调节。基于这些发现，我们建议在解释交叉滞后效应的大小时，使用.03（小效应）、.07（中效应）和.12（大效应）作为基准值，适用于 CLPM 和 RI-CLPM。除了有助于解释结果外，本研究的发现还将通过提供进行功效分析和估计最小所需样本量所需的信息，帮助研究人员计划研究。（PsycInfo 数据库记录（c）2024 APA，保留所有权利）。
