Xiao Yue, Wang Pujue, Liu Hongyun
Department of Educational Psychology, Faculty of Education, East China Normal University.
Faculty of Psychology, Beijing Normal University.
Psychol Methods. 2023 Aug 10. doi: 10.1037/met0000608.
Intensive longitudinal studies are becoming increasingly popular because of their potential for studying the individual dynamics of psychological processes. However, measures used in such studies are quite susceptible to measurement error due to the short lengths and therefore their psychometric properties, such as reliability, are of great concern. Most existing approaches for assessing reliability are not appropriate for the intensive longitudinal data (ILD) because of the conflation of inter- and intra-individual variations or the difficulty in handling interindividual differences. In addition, measurement models are always relegated or omitted in the ILD modeling approaches. Therefore, in this article, we introduce a two-level random dynamic measurement (2RDM) model for ILD, which takes into account measurement models for key variables of interest. Then we discuss how to derive the within-person and between-person reliabilities for items and scales in the context of the 2RDM model. A small simulation study is presented to illustrate the implementation of the 2RDM model and reliability estimation. An empirical study is then provided to demonstrate the application of the proposed approach for multidimensional scales, in which we calculated the within- and between-person reliabilities for both items and subscales of a short version of the Perceived Stress Scale and found large individual differences in the within-person reliabilities. We conclude by discussing the advantages and considerations of the proposed approach in practice. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
密集纵向研究因其在研究心理过程个体动态方面的潜力而越来越受欢迎。然而,此类研究中使用的测量方法由于长度较短,很容易受到测量误差的影响,因此其心理测量特性,如信度,备受关注。由于个体间和个体内变异的混淆或处理个体间差异的困难,大多数现有的评估信度的方法不适用于密集纵向数据(ILD)。此外,在ILD建模方法中,测量模型总是被贬低或省略。因此,在本文中,我们为ILD引入了一种两级随机动态测量(2RDM)模型,该模型考虑了感兴趣的关键变量的测量模型。然后,我们讨论了如何在2RDM模型的背景下推导项目和量表的个体内和个体间信度。我们进行了一个小型模拟研究来说明2RDM模型的实现和信度估计。随后提供了一项实证研究,以证明所提出的方法在多维量表中的应用,在该研究中,我们计算了感知压力量表简版的项目和子量表的个体内和个体间信度,发现个体内信度存在很大的个体差异。我们通过讨论所提出方法在实践中的优点和注意事项来结束本文。(PsycInfo数据库记录(c)2023美国心理学会,保留所有权利)