Graphical models for clustered binary and continuous responses Chapter uri icon


MeSH Major

  • Behavioral Medicine
  • Health Behavior
  • Translational Medical Research


  • Graphical models for clustered data mixed with discrete and continuous responses are developed. Discrete responses are assumed to be regulated by some latent continuous variables and particular link functions are used to describe the regulatory mechanisms. Inferential procedures are constructed using the full-information maximum likelihood estimation and observed/empirical Fisher information matrices. Implementation is carried out by stochastic versions of the generalized EM algorithm. As an illustrative application, clustered data from a developmental toxicity study is re-investigated using the directed graphical model and the proposed algorithms. A new interesting directed association between two mixed outcomes reveals. The proposed methods also apply to cross-sectional data with discrete and continuous responses. © 2011 Springer-Verlag Berlin Heidelberg.

publication date

  • December 2011



  • Book Chapter


Digital Object Identifier (DOI)

  • 10.1007/978-3-7908-2628-9_19

Additional Document Info

start page

  • 305

end page

  • 321