A LATENT FACTOR MODEL FOR SPATIAL DATA WITH INFORMATIVE MISSINGNESS.

ABSTRACT: A large amount of data is typically collected during a periodontal exam. Analyzing these data poses several challenges. Several types of measurements are taken at many locations throughout the mouth. These spatially-referenced data are a mix of binary and continuous responses, making joint modeling difficult. Also, most patients have missing teeth. Periodontal disease is a leading cause of tooth loss, so it is likely that the number and location of missing teeth informs about the patient's periodontal health. In this paper we develop a multivariate spatial framework for these data which jointly models the binary and continuous responses as a function of a single latent spatial process representing general periodontal health. We also use the latent spatial process to model the location of m

SUBMITTER: Reich BJ 

PROVIDER: S-EPMC2901904 | biostudies-literature | 2010 Mar

REPOSITORIES: biostudies-literature