Aytürk Ezgi, Cham Heining, Jennings Patricia A, Brown Joshua L
Fordham University, Bronx, NY, USA.
University of Virginia, Charlottesville, VA, USA.
Educ Psychol Meas. 2020 Apr;80(2):262-292. doi: 10.1177/0013164419865017. Epub 2019 Jul 24.
Methods to handle ordered-categorical indicators in latent variable interactions have been developed, yet they have not been widely applied. This article compares the performance of two popular latent variable interaction modeling approaches in handling ordered-categorical indicators: unconstrained product indicator (UPI) and latent moderated structural equations (LMS). We conducted a simulation study across sample sizes, indicators' distributions and category conditions. We also studied four strategies to create sets of product indicators for UPI. Results supported using a parceling strategy to create product indicators in the UPI approach or using the LMS approach when the categorical indicators are symmetrically distributed. We applied these models to study the interaction effect between third- to fifth-grade students' social skills improvement and teacher-student closeness on their state English language arts test scores.
处理潜在变量交互中有序分类指标的方法已经得到发展,但尚未得到广泛应用。本文比较了两种流行的潜在变量交互建模方法在处理有序分类指标方面的性能:无约束乘积指标(UPI)和潜在调节结构方程(LMS)。我们针对样本量、指标分布和类别条件进行了一项模拟研究。我们还研究了为UPI创建乘积指标集的四种策略。结果支持在UPI方法中使用打包策略来创建乘积指标,或者在分类指标对称分布时使用LMS方法。我们应用这些模型来研究三至五年级学生的社交技能提升与师生亲密程度对其州英语语言艺术测试成绩的交互作用。