ABSTRACT

Structural equation modeling (SEM) software commonly report information criteria, like the AIC, for the model under investigation and for the unconstrained/saturated model. With these criteria, (non-)nested models can be compared. This comes down to evaluating equalities (e.g., setting some paths equal or to 0). These criteria cannot evaluate inequality restrictions on the parameters, while the AIC-type criterion called GORICA can. For example, GORICA can evaluate the hypothesis stating that one predictor has more (standardized) strength than some other predictors. This paper illustrates inequality-constrained hypothesis-evaluation in SEM models using the GORICA (in R). Examples will be presented for confirmatory factor analysis, latent regression, and multigroup latent regression.

摘要

结构方程建模 (SEM) 软件通常报告正在研究的模型和无约束/饱和模型的信息标准，如 AIC。使用这些标准，可以比较（非）嵌套模型。这归结为评估相等性（例如，将某些路径设置为等于或等于 0）。这些标准不能评估参数的不等式限制，而称为 GORICA 的 AIC 类型标准可以。例如，GORICA 可以评估假设一个预测器比其他一些预测器具有更多（标准化）强度。本文说明了使用 GORICA（在 R 中）的 SEM 模型中的不平等约束假设评估。将提供验证性因素分析、潜在回归和多组潜在回归的示例。