title: A comparison of three methods for calculating confidence intervals for the benchmark dose.
abstract: Various methods exist to calculate confidence intervals for the benchmark dose in risk analysis. This study compares the performance of three such methods in fitting nonlinear dose-response models: the delta method, the likelihood-ratio method, and the bootstrap method. A data set from a developmental toxicity test with continuous, ordinal, and quantal dose-response data is used for the comparison of these methods. Nonlinear dose-response models, with various shapes, were fitted to these data. The results indicate that a few thousand runs are generally needed to get stable confidence limits when using the bootstrap method. Further, the bootstrap and the likelihood-ratio method were found to give fairly similar results. The delta method, however, resulted in some cases in different (usually narrower) intervals, and appears unreliable for nonlinear dose-response models. Since the bootstrap method is more time consuming than the likelihood-ratio method, the latter is more attractive for routine dose-response analysis. In the context of a probabilistic risk assessment the bootstrap method has the advantage that it directly links to Monte Carlo analysis.
authors.affiliation: Department of Methodology and Statistics, Utrecht University, Utrecht, the Netherlands.
authors.forename: Mirjam
authors.initials: M
authors.lastname: Moerbeek
authors.forename: Aldert H
authors.initials: AH
authors.lastname: Piersma
authors.forename: Wout
authors.initials: W
authors.lastname: Slob
mesh_terms: D000818:Animals; D019985:Benchmarking; D016001:Confidence Intervals; D004305:Dose-Response Relationship, Drug; D005314:Embryonic and Fetal Development / Q000187:drug effects; D005260:Female; D016013:Likelihood Functions; D008297:Male; D009010:Monte Carlo Method; D019055:No-Observed-Adverse-Effect Level; D017711:Nonlinear Dynamics; D011247:Pregnancy; D051381:Rats; D012306:Risk; D018675:Toxicity Tests / Q000706:statistics & numerical data