Estimation for polynomial structural equation models
Estimation for polynomial structural equation models
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DOI：
10.2307/2669475
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发表时间：
2000-09-01
影响因子：
3.7
通讯作者：
Amemiya, Y
中科院分区：
文献类型：
--
作者：
Wall, MM;Amemiya, Y
结构方程分析是社会和行为科学研究中应用最广泛的统计方法之一，已成为市场营销中流行的工具。考虑非线性结构模型的主题需求已经有很好的文献记载。但目前的拟合程序仅适用于有限类别的模型。本文对一般多项式结构方程模型提出了一种系统的统计方法。新方法采用了一种矩量法，类似于误差变量回归中使用的矩量法，从测量模型拟合中估计因子得分。导出了该估计量的渐近性质，并引入了具有较好小样本性质的改进估计量。仿真研究报告显示了该程序的有效性，并将其性能与其他方法进行了比较。本文还讨论了预防药物滥用研究中的一个例子。
Structural equation analysis is one of the most widely used statistical methods in social and behavioral science research and has become a popular tool in marketing. Subject matter needs for considering nonlinear structural models have been well documented. But current fitting procedures are available only for a limited class of models. In this article a systematic statistical approach is developed for the general polynomial, structural equation model. The new procedure applies a method of moments procedure similar to the one used in errors-in-variables regression to the factor score estimates from the measurement model fit. The asymptotic properties of the estimator are derived, and a modified estimator with better small-sample properties is introduced. Simulation studies are reported to show the usefulness of the procedure and to compare its performance to other methods. An example from a substance abuse prevention study is also discussed.