Optimal designs for health risk assessments using fractional polynomial models

Víctor Casero-Alonso, Jesús López–Fidalgo, Weng Kee Wong

研究成果: Article同行評審

1 引文 斯高帕斯(Scopus)

摘要

Fractional polynomials (FP) have been shown to be more flexible than polynomial models for fitting data from an univariate regression model with a continuous outcome but design issues for FP models have lagged. We focus on FPs with a single variable and construct D-optimal designs for estimating model parameters and I-optimal designs for prediction over a user-specified region of the design space. Some analytic results are given, along with a discussion on model uncertainty. In addition, we provide an applet to facilitate users find tailor made optimal designs for their problems. As applications, we construct optimal designs for three studies that used FPs to model risk assessments of (a) testosterone levels from magnesium accumulation in certain areas of the brains in songbirds, (b) rats subject to exposure of different chemicals, and (c) hormetic effects due to small toxic exposure. In each case, we elaborate the benefits of having an optimal design in terms of cost and quality of the statistical inference.

原文English
頁(從 - 到)2695-2710
頁數16
期刊Stochastic Environmental Research and Risk Assessment
36
發行號9
DOIs
出版狀態Published - 2022 9月

All Science Journal Classification (ASJC) codes

  • 環境工程
  • 環境化學
  • 水科學與技術
  • 安全、風險、可靠性和品質
  • 一般環境科學

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