A nonparametric Bayesian modeling approach for cytogenetic dosimetry.

Published

Journal Article

In cytogenetic dosimetry, samples of cell cultures are exposed to a range of doses of a given agent. In each sample at each dose level, some measure of cell disability is recorded. The objective is to develop models that explain cell response to dose. Such models can be used to predict response at unobserved doses. More important, such models can provide inference for unknown exposure doses given the observed responses. Typically, cell disability is viewed as a Poisson count, but in the present work, a more appropriate response is a categorical classification. In the literature, modeling in this case is very limited. What exists is purely parametric. We propose a fully Bayesian nonparametric approach to this problem. We offer comparison with a parametric model through a simulation study and the analysis of a real dataset modeling blood cultures exposed to radiation where classification is with regard to number of micronuclei per cell.

Full Text

Duke Authors

Cited Authors

  • Kottas, A; Branco, MD; Gelfand, AE

Published Date

  • September 2002

Published In

Volume / Issue

  • 58 / 3

Start / End Page

  • 593 - 600

PubMed ID

  • 12229994

Pubmed Central ID

  • 12229994

Electronic International Standard Serial Number (EISSN)

  • 1541-0420

International Standard Serial Number (ISSN)

  • 0006-341X

Digital Object Identifier (DOI)

  • 10.1111/j.0006-341x.2002.00593.x

Language

  • eng