Model Selection and Estimation with Quantal-Response Data in Benchmark Risk Assessment.
Risk Anal
; 37(4): 716-732, 2017 04.
Article
em En
| MEDLINE
| ID: mdl-27322778
ABSTRACT
This article describes several approaches for estimating the benchmark dose (BMD) in a risk assessment study with quantal dose-response data and when there are competing model classes for the dose-response function. Strategies involving a two-step approach, a model-averaging approach, a focused-inference approach, and a nonparametric approach based on a PAVA-based estimator of the dose-response function are described and compared. Attention is raised to the perils involved in data "double-dipping" and the need to adjust for the model-selection stage in the estimation procedure. Simulation results are presented comparing the performance of five model selectors and eight BMD estimators. An illustration using a real quantal-response data set from a carcinogenecity study is provided.
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Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Medição de Risco
/
Relação Dose-Resposta a Droga
Idioma:
En
Ano de publicação:
2017
Tipo de documento:
Article