Nonparametric Bayesian methods for benchmark dose estimation
Guha, N; Roy, A; Kopylev, L; Fox, J; Spassova, M; White, P
HERO ID
2328095
Reference Type
Journal Article
Year
2013
Language
English
PMID
| HERO ID | 2328095 |
|---|---|
| In Press | No |
| Year | 2013 |
| Title | Nonparametric Bayesian methods for benchmark dose estimation |
| Authors | Guha, N; Roy, A; Kopylev, L; Fox, J; Spassova, M; White, P |
| Journal | Risk Analysis |
| Volume | 33 |
| Issue | 9 |
| Page Numbers | 1608-1619 |
| Abstract | The article proposes and investigates the performance of two Bayesian nonparametric estimation procedures in the context of benchmark dose estimation in toxicological animal experiments. The methodology is illustrated using several existing animal dose-response data sets and is compared with traditional parametric methods available in standard benchmark dose estimation software (BMDS), as well as with a published model-averaging approach and a frequentist nonparametric approach. These comparisons together with simulation studies suggest that the nonparametric methods provide a lot of flexibility in terms of model fit and can be a very useful tool in benchmark dose estimation studies, especially when standard parametric models fail to fit to the data adequately. |
| Doi | 10.1111/risa.12004 |
| Pmid | 23339666 |
| Is Certified Translation | No |
| Dupe Override | No |
| Comments | Journal: Risk analysis : an official publication of the Society for Risk Analysis ISSN: 1539-6924 |
| Is Public | Yes |
| Language Text | English |
| Keyword | BMDL; BMDS software; dirichlet distribution; integrated Brownian motion |