Simulation-based assessment of model selection criteria during the application of benchmark dose method to quantal response data
暂无分享,去创建一个
Kaoru Inoue | Keita Yoshii | Hiroshi Nishiura | Takayuki Yamaguchi | Akihiko Hirose | H. Nishiura | A. Hirose | Kaoru Inoue | Takayuki Yamaguchi | Keita Yoshii
[1] Joseph G. Ibrahim,et al. Bayesian Model Averaging With Applications to Benchmark Dose Estimation for Arsenic in Drinking Water , 2006 .
[2] Jiri Aubrecht,et al. Comparison of toxicogenomics and traditional approaches to inform mode of action and points of departure in human health risk assessment of benzo[a]pyrene in drinking water , 2015, Critical reviews in toxicology.
[3] Adrian E. Raftery,et al. Bayesian model averaging: a tutorial (with comments by M. Clyde, David Draper and E. I. George, and a rejoinder by the authors , 1999 .
[4] H. Akaike. A Bayesian analysis of the minimum AIC procedure , 1978 .
[5] Matthew W Wheeler,et al. Properties of Model‐Averaged BMDLs: A Study of Model Averaging in Dichotomous Response Risk Estimation , 2007, Risk analysis : an official publication of the Society for Risk Analysis.
[6] Salomon Sand,et al. The current state of knowledge on the use of the benchmark dose concept in risk assessment , 2008, Journal of applied toxicology : JAT.
[7] B C Allen,et al. Dose-response assessment for developmental toxicity. III. Statistical models. , 1994, Fundamental and applied toxicology : official journal of the Society of Toxicology.
[8] R. Hertzberg,et al. A new method for determining allowable daily intakes. , 1986, Fundamental and applied toxicology : official journal of the Society of Toxicology.
[9] N. Hjort,et al. Frequentist Model Average Estimators , 2003 .
[10] Matthew W Wheeler,et al. An empirical comparison of low-dose extrapolation from points of departure (PoD) compared to extrapolations based upon methods that account for model uncertainty. , 2013, Regulatory toxicology and pharmacology : RTP.
[11] A. Ono,et al. Validation of the statistical parameters and model selection criteria of the benchmark dose methods for the evaluation of various endpoints in repeated-dose toxicity studies , 2019, Fundamental Toxicological Sciences.
[12] T. Byford. Principles for modelling dose-response for the risk assessment of chemicals , 2014 .
[13] Adrian E. Raftery,et al. Bayesian Model Averaging: A Tutorial , 2016 .
[14] David R. Anderson,et al. Understanding AIC and BIC in Model Selection , 2004 .
[15] Stefan D Muri,et al. The benchmark dose approach in food risk assessment: is it applicable and worthwhile? , 2009, Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association.
[16] Statistical uncertainty in the no-observed-adverse-effect level , 1989 .
[17] D. Barnes,et al. Reference dose (RfD): description and use in health risk assessments. , 1988, Regulatory toxicology and pharmacology : RTP.
[18] Fred A. Wright,et al. Standardizing Benchmark Dose Calculations to Improve Science-Based Decisions in Human Health Assessments , 2014, Environmental health perspectives.
[19] Kan Shao,et al. Potential Uncertainty Reduction in Model‐Averaged Benchmark Dose Estimates Informed by an Additional Dose Study , 2011, Risk analysis : an official publication of the Society for Risk Analysis.
[20] W Leisenring,et al. Statistical properties of the NOAEL. , 1992, Regulatory toxicology and pharmacology : RTP.
[21] F. Massey. The Kolmogorov-Smirnov Test for Goodness of Fit , 1951 .
[22] Hilde van der Togt,et al. Publisher's Note , 2003, J. Netw. Comput. Appl..
[23] Salomon Sand,et al. Evaluation of the benchmark dose method for dichotomous data: model dependence and model selection. , 2002, Regulatory toxicology and pharmacology : RTP.
[24] Lingling An,et al. Information‐theoretic model‐averaged benchmark dose analysis in environmental risk assessment , 2013, Environmetrics.
[25] D W Gaylor,et al. Issues in qualitative and quantitative risk analysis for developmental toxicology. , 1988, Risk analysis : an official publication of the Society for Risk Analysis.
[26] C. Kimmel,et al. Dose-response assessment for developmental toxicity. II. Comparison of generic benchmark dose estimates with no observed adverse effect levels. , 1994, Fundamental and applied toxicology : official journal of the Society of Toxicology.
[27] R. Zamar,et al. A multivariate Kolmogorov-Smirnov test of goodness of fit , 1997 .
[28] T. Lewandowski,et al. Derivation of the critical effect size/benchmark response for the dose-response analysis of the uptake of radioactive iodine in the human thyroid. , 2016, Toxicology letters.
[29] K. G. Brown,et al. Statistical uncertainty in the no-observed-adverse-effect level. , 1989, Fundamental and applied toxicology : official journal of the Society of Toxicology.
[30] R L Kodell,et al. Incorporating model uncertainties along with data uncertainties in microbial risk assessment. , 2000, Regulatory toxicology and pharmacology : RTP.
[31] A. John Bailer,et al. Comparing model averaging with other model selection strategies for benchmark dose estimation , 2009, Environmental and Ecological Statistics.
[32] A. John Bailer,et al. Model Averaging Software for Dichotomous Dose Response Risk Estimation , 2008 .
[33] N. L. Johnson,et al. The probability integral transformation when parameters are estimated from the sample. , 1948, Biometrika.
[34] Matthew W Wheeler,et al. Model Uncertainty and Risk Estimation for Experimental Studies of Quantal Responses , 2005, Risk analysis : an official publication of the Society for Risk Analysis.
[35] Daniel Turek,et al. Model-Averaged Profile Likelihood Intervals , 2012 .
[36] José Cortiñas Abrahantes,et al. Update: use of the benchmark dose approach in risk assessment , 2017, EFSA journal. European Food Safety Authority.
[37] Kan Shao,et al. Model Uncertainty and Bayesian Model Averaged Benchmark Dose Estimation for Continuous Data , 2014, Risk analysis : an official publication of the Society for Risk Analysis.
[38] Jian Bi. Using the benchmark dose (BMD) methodology to determine an appropriate reduction of certain ingredients in food products. , 2010, Journal of food science.