The importance of isomorphism for conclusions about homology: A Bayesian multilevel structural equation modeling approach with ordinal indicators

Supplementary files. v2. Adds excel table of MC results v1. Guenole, N. (in review). The importance of isomorphism for conclusions about homology. A bayesian multilevel structural equation modeling approach with ordinal indicators. Description: Van de Schoot et al. (2015) observed that variance parameters estimated with Bayesian methods can be subject to spikes (i.e., extreme estimates) especially for variance terms, which inflate parameter estimates. To permit readers to evaluate whether this occurred in the current Monte Carlo study this file contains trace plots for the within and between latent variance and latent residual variance parameters for a sample run from each of the 384 cells in the design. Each file is numbered according to the design cell represents and contains a panel plot of four figures a) within latent variance, b) within latent residual variance, c) between latent variance, and d) between latent residual variance. References Van de Schoot, R., Broere, J.J., Perryck, K., Zondervan-Zwijnenburg, M., & Van Loey, N. (2015). Analyzing Small Data Sets using Bayesian Estimation: The case of posttraumatic stress symptoms following mechanical ventilation in burn survivors. European Journal of Psychotraumatology, 6: 25216 - http://dx.doi.org/10.3402/ejpt.v6.25216

补充文件（版本2）：新增蒙特卡洛（Monte Carlo, MC）模拟结果Excel表格（版本1）。
相关论文：Guenole, N.（待刊）：《同构性对同源性结论的重要性：基于序次指标的贝叶斯多水平结构方程建模方法》。
数据集说明：Van de Schoot等（2015）研究发现，采用贝叶斯方法估计的方差参数易出现尖峰估计值（即极端数值），尤其针对方差项时，该现象会导致参数估计结果被夸大。为便于读者评估本次蒙特卡洛研究中是否出现此类估计偏差，本文件包含了实验设计中384个单元格各单次抽样样本的组内潜在方差、组间潜在方差以及潜在残差方差参数的轨迹图。每个文件均以其对应的设计单元格编号命名，内含由四幅子图组成的面板图：a) 组内潜在方差，b) 组内潜在残差方差，c) 组间潜在方差，d) 组间潜在残差方差。
参考文献：Van de Schoot, R.、Broere, J.J.、Perryck, K.、Zondervan-Zwijnenburg, M. 与 Van Loey, N.（2015）：《使用贝叶斯估计分析小数据集：烧伤幸存者机械通气后创伤后应激症状案例》，《欧洲创伤心理学杂志》，6: 25216 — http://dx.doi.org/10.3402/ejpt.v6.25216