A Bayesian analysis of mixture structural equation models with non-ignorable missing responses and covariates.

@article{Cai2010ABA,
  title={A Bayesian analysis of mixture structural equation models with non-ignorable missing responses and covariates.},
  author={Jingheng Cai and Xinyuan Song and Yih-Ing Hser},
  journal={Statistics in medicine},
  year={2010},
  volume={29 18},
  pages={
          1861-74
        }
}
In behavioral, biomedical, and social-psychological sciences, it is common to encounter latent variables and heterogeneous data. Mixture structural equation models (SEMs) are very useful methods to analyze these kinds of data. Moreover, the presence of missing data, including both missing responses and missing covariates, is an important issue in practical research. However, limited work has been done on the analysis of mixture SEMs with non-ignorable missing responses and covariates. The main… 
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