A comparison of methods for estimating quadratic effects in nonlinear structural equation models.
A comparison of methods for estimating quadratic effects in nonlinear structural equation models.
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DOI：
10.1037/a0027539
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发表时间：
2012-06
影响因子：
7
通讯作者：
Hsu, Jui-Chen
中科院分区：
文献类型：
--
作者：
Harring, Jeffrey R.;Weiss, Brandi A.;Hsu, Jui-Chen
进行了两次Monte Carlo模拟，以比较潜变量回归模型中二次效应假设的估计和检验方法。本研究中考虑的方法是（a）使用潜变量评分的2阶段调节回归方法，（B）无约束产品指标方法，（c）潜调节结构方程方法，（d）完全贝叶斯方法，（e）边际最大似然估计。在5种估计方法中，发现总体而言，基于最大似然估计和贝叶斯方法的方法在偏倚、均方根误差、标准误比、把握度和I类错误控制方面表现最佳，尽管观察到了关键差异。重点介绍了各种方法之间的相似之处和差异，并阐述了一般性建议。作为比较，所有5种方法都适合于教育阅读数据的潜在二次模型的重新参数化版本。
Two Monte Carlo simulations were performed to compare methods for estimating and testing hypotheses of quadratic effects in latent variable regression models. The methods considered in the current study were (a) a 2-stage moderated regression approach using latent variable scores, (b) an unconstrained product indicator approach, (c) a latent moderated structural equation method, (d) a fully Bayesian approach, and (e) marginal maximum likelihood estimation. Of the 5 estimation methods, it was found that overall the methods based on maximum likelihood estimation and the Bayesian approach performed best in terms of bias, root-mean-square error, standard error ratios, power, and Type I error control, although key differences were observed. Similarities as well as disparities among methods are highlight and general recommendations articulated. As a point of comparison, all 5 approaches were fit to a reparameterized version of the latent quadratic model to educational reading data.
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影响因子：
22.4
作者：
JACCARD, J;WAN, CK
通讯作者：
WAN, CK
影响因子：
7
作者：
Curran, PJ;West, SG;Finch, JF
通讯作者：
Finch, JF
DOI：
10.1207/s15328007sem0801_3
发表时间：
2001-01-01
影响因子：
6
作者：
Algina, James;Moulder, Bradley C.
通讯作者：
Moulder, Bradley C.
影响因子：
22.4
作者：
HU, LT;BENTLER, PM;KANO, Y
通讯作者：
KANO, Y
影响因子：
2.4
作者：
Brooks, SP;Gelman, A
通讯作者：
Gelman, A