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http://hdl.handle.net/1942/4026
Title: | Model averaging using fractional polynomials to estimate a safe level of exposure | Authors: | FAES, Christel AERTS, Marc GEYS, Helena MOLENBERGHS, Geert |
Issue Date: | 2007 | Publisher: | BLACKWELL PUBLISHING | Source: | RISK ANALYSIS, 27(1). p. 111-123 | Abstract: | Quantitative risk assessment involves the determination of a safe level of exposure. Recent techniques use the estimated dose-response curve to estimate such a safe dose level. Although such methods have attractive features, a low-dose extrapolation is highly dependent on the model choice. Fractional polynomials,((1)) basically being a set of (generalized) linear models, are a nice extension of classical polynomials, providing the necessary flexibility to estimate the dose-response curve. Typically, one selects the best-fitting model in this set of polynomials and proceeds as if no model selection were carried out. We show that model averaging using a set of fractional polynomials reduces bias and has better precision in estimating a safe level of exposure (say, the benchmark dose), as compared to an estimator from the selected best model. To estimate a lower limit of this benchmark dose, an approximation of the variance of the model-averaged estimator, as proposed by Burnham and Anderson,((2)) can be used. However, this is a conservative method, often resulting in unrealistically low safe doses. Therefore, a bootstrap-based method to more accurately estimate the variance of the model averaged parameter is proposed. | Notes: | Hasselt Univ, Ctr Stat, Diepenbeek, Belgium. Johnson & Johnson, PRD Biometr & Clin Informat, Beerse, Belgium.FAES, C, Hasselt Univ, Ctr Stat, Agoralaan 1, Diepenbeek, Belgium.christel.faes@uhasselt.be | Keywords: | benchmark dose; fractional polynomials; model averaging; risk assessment;benchmark dose; fractional polynomials; model averaging; risk assessment | Document URI: | http://hdl.handle.net/1942/4026 | ISSN: | 0272-4332 | e-ISSN: | 1539-6924 | DOI: | 10.1111/j.1539-6924.2006.00863.x | ISI #: | 000244798100012 | Rights: | (C) 2007 Society for Risk Analysis | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2008 |
Appears in Collections: | Research publications |
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Faes_et_al-2007-Risk_Analysis.pdf Restricted Access | Published version | 397.31 kB | Adobe PDF | View/Open Request a copy |
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