[DFS10a] Contributions to Bayesian Structural Equation Modeling

Conférence Internationale avec comité de lecture : COMPSTAT'2010, 19th International Conference on Computational Statistics, Paris, August 2010, pp.469-476, Paris, france,
Résumé: Structural equation models (SEMs) are multivariate latent variable models used to model causality structures in data. A Bayesian estimation and validation of SEMs is proposed and identi ability of parameters is studied. The latter study shows that latent variables should be standardized in the nalysis to ensure identi fiability. This heuristics is in fact introduced to deal with complex identi ability constraints. To illustrate the point, identi ability constraints are calculated in a marketing application, in which posterior draws of the constraints are derived from the posterior conditional distributions of parameters.

Equipe: msdma


@inproceedings {
title="{Contributions to Bayesian Structural Equation Modeling}",
author=" S. Demeyer and N. Fischer and G. Saporta ",
booktitle="{COMPSTAT'2010, 19th International Conference on Computational Statistics, Paris}",
address="Paris, france",