Julien P Irmer, Andreas G Klein, Karin Schermelleh-Engel
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引用次数: 0
摘要
基于模型推导模拟的功率估计(MSPE)方法是一种新的功率估计通用方法(Irmer 等人,2024 年)。MSPE 是专为非线性结构方程模型(SEM)的幂估计而开发的,但也可使用 R 软件包 powerNLSEM 用于线性 SEM 和显式模型。首先介绍了有关 MSPE 和新的自适应算法的一些信息,该算法可通过模拟自动选择样本大小以获得最佳的预测功率,然后介绍了如何使用 powerNLSEM 软件包对二次和交互 SEM (QISEM) 进行 MSPE。我们演示了四种方法的功率估计,即潜在调节结构方程 (LMS)、无约束乘积指标 (UPI)、简单因子得分回归 (FSR) 和 QISEM 的尺度回归 (SR) 方法。在两项模拟研究中,我们强调了 MSPE 对所有四种方法的性能,并将其应用于两个具有不同复杂性和可靠性的 QISEM。此外,我们还通过模拟性能评估来证明新开发的自适应搜索算法的设置是合理的。总体而言,使用自适应方法的 MSPE 在偏差和 I 类错误率方面表现良好。
Estimating power in complex nonlinear structural equation modeling including moderation effects: The powerNLSEM R-package.
The model-implied simulation-based power estimation (MSPE) approach is a new general method for power estimation (Irmer et al., 2024). MSPE was developed especially for power estimation of non-linear structural equation models (SEM), but it also can be applied to linear SEM and manifest models using the R package powerNLSEM. After first providing some information about MSPE and the new adaptive algorithm that automatically selects sample sizes for the best prediction of power using simulation, a tutorial on how to conduct the MSPE for quadratic and interaction SEM (QISEM) using the powerNLSEM package is provided. Power estimation is demonstrated for four methods, latent moderated structural equations (LMS), the unconstrained product indicator (UPI), a simple factor score regression (FSR), and a scale regression (SR) approach to QISEM. In two simulation studies, we highlight the performance of the MSPE for all four methods applied to two QISEM with varying complexity and reliability. Further, we justify the settings of the newly developed adaptive search algorithm via performance evaluations using simulation. Overall, the MSPE using the adaptive approach performs well in terms of bias and Type I error rates.
期刊介绍:
ACS Applied Energy Materials is an interdisciplinary journal publishing original research covering all aspects of materials, engineering, chemistry, physics and biology relevant to energy conversion and storage. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important energy applications.