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

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.