Nonparametric estimation of benchmark doses in environmental risk assessment

Environmetrics

Volumn 23, Issue 8, 2012, Pages 717-728

  Piegorsch, Walter W ^a,b   Xiong, Hui ^a   Bhattacharya, Rabi N ^a,b   Lin, Lizhen ^b  

^a UNIVERSITY OF ARIZONA   (United States)

^b University of Arizona   (United States)

Author keywords

Benchmark analysis; Bootstrap confidence limits; Dose response analysis; Isotonic regression; Pool adjacent violators algorithm

Indexed keywords

ALGORITHM; BENCHMARKING; BOOTSTRAPPING; CANCER; DOSE-RESPONSE RELATIONSHIP; ENVIRONMENTAL RISK; EXPERIMENTAL STUDY; HEALTH RISK; REGRESSION ANALYSIS; RISK ASSESSMENT;

EID: 84871697108     PISSN: 11804009     EISSN: 1099095X     Source Type: Journal    
DOI: 10.1002/env.2175     Document Type: Article

References (48)

1. Ayer M, Brunk HD, Ewing GM, Reid WT, Silverman E.1955.An empirical distribution function for sampling with incomplete information. Annals of Mathematical Statistics 26: 641-647.
2. Bailer AJ, Noble RB, Wheeler MW.2005. Model uncertainty and risk estimation for experimental studies of quantal responses. Risk Analysis 25: 291-299.
3. Bailer AJ, Smith RJ.1994. Estimating upper confidence limits for extra risk in quantal multistage models. Risk Analysis 14: 1001-1010.
4. Bhattacharya RN, Kong M.2007. Consistency and asymptotic normality of the estimated effective doses in bioassay. Journal of Statistical Planning and Inference 137: 643-658.
5. Bhattacharya RN, Lin L.2010. An adaptive nonparametric method in benchmark analysis for bioassay and environmental studies. Statistics and Probability Letters 80: 1947-1953.
6. Bhattacharya RN, Lin L.2011. Nonparametric benchmark analysis in risk assessment: a comparative study by simulation and data analysis. Sankhyā, Series B 73: 144-163.
7. Buckley BE, Piegorsch WW.2008. Simultaneous confidence bands for Abbott-adjusted quantal response models. Statistical Methodology 5: 209-219.
8. Buckley BE, Piegorsch WW, West RW.2009. Confidence limits on one-stage model parameters in benchmark risk assessment. Environmental and Ecological Statistics 16: 53-62.
9. Crump KS.1984. A new method for determining allowable daily intake. Fundamental and Applied Toxicology 4: 854-871.
10. Crump KS.1995. Calculation of benchmark doses from continuous data. Risk Analysis 15: 79-89.
11. Crump KS. 2012. Benchmark analysis. In Encyclopedia of Environmentrics, Vol.1, El-Shaarawi AH, Piegorsch WW (eds), 2nd edition, John Wiley & Sons: Chichester, U.K.; 191-198.
12. Dette H, Neumeyer N, Pilz KF.2005. A note on nonparametric estimation of the effective dose in quantal bioassay. Journal of the American Statistical Association 100: 503-510.
13. Dette H, Scheder R.2010. A finite sample comparison of nonparametric estimates of the effective dose in quantal bioassay. Journal of Statistical Computation and Simulation 80: 527-544.
14. DiCiccio TJ, Efron B.1996. Bootstrap confidence intervals (with discussion). Statistical Science 11: 189-228.
15. DiCiccio TJ, Romano JP.1988. A review of bootstrap confidence intervals. Journal of the Royal Statistical Society, Series B (Methodological) 50: 338-354.
16. Faes C, Aerts M, Geys H, Molenberghs G.2007. Model averaging using fractional polynomials to estimate a safe level of exposure. Risk Analysis 27: 111-123.
17. Faustman EM, Bartell SM.1997. Review of noncancer risk assessment: applications of benchmark dose methods. Human and Ecological Risk Assessment 3: 893-920.
18. Green PJ, Silverman BW.1994. Nonparametric Regression and Generalized Linear Models. Chapman & Hall: London, U.K.
19. Izadi H, Grundy JE, Bose R.2012. Evaluation of the benchmark dose for point of departure determination for a variety of chemical classes in applied regulatory settings. Risk Analysis 32: 830-835.
20. Kang S-H, Kodell RL, Chen JJ.2000. Incorporating model uncertainties along with data uncertainties in microbial risk assessment. Regulatory Toxicology and Pharmacology 32: 68-72.
21. Kodell RL.2005. Managing uncertainty in health risk assessment. International Journal of Risk Assessment and Management 14: 193-205.
22. 10. Environmental and Ecological Statistics 16: 3-12.
23. Krewski D, Gaylor D, Szyszkowicz M.1991. A model-free approach to low dose extrapolation. Environmental Health Perspectives 90: 279-285.
24. Moerbeek M, Piersma AH, Slob W.2004. A comparison of three methods for calculating confidence intervals for the benchmark dose. Risk Analysis 24: 31-40.
25. Moon H, Kim H-J, Chen JJ, Kodell RL.2005. Model averaging using the Kullback information criterion in estimating effective doses for microbial infection and illness. Risk Analysis 25: 1147-1159.
26. Morales KH, Ibrahim JG, Chen C-J, Ryan LM.2006. Bayesian model averaging with applications to benchmark dose estimation for arsenic in drinking water. Journal of the American Statistical Association 101: 9-17.
27. Mukerjee H.1988. Monotone nonparametric regression. Annals of Statistics 16: 741-750.
28. Müller H-G, Schmitt T.1988. Kernel and probit estimates in quantal bioassay. Journal of the American Statistical Association 83: 750-759.
29. OECD. 2010.OECD Guidelines for the Testing of Chemicals, Section 2 - Effects on Biotic Systems. Test No. 223: Avian Acute Oral Toxicity Test. Organisation For Economic Co-operation and Development Publishing: Paris. DOI: 10.1787/20745761.
30. Opsomer JD. 2012. Nonparametric regression model. In Encyclopedia of Environmetrics, Vol.4, El-Shaarawi AH, Piegorsch WW (eds), 2nd edition. John Wiley & Sons: Chichester, UK; 1798-1811.
31. Piegorsch WW. 2012. Quantal response data. In Encyclopedia of Environmetrics, Vol.4, El-Shaarawi AH, Piegorsch WW (eds), 2nd edition. John Wiley & Sons: Chichester, UK; 2065-2067.
32. Piegorsch WW, Bailer AJ.2005. Analyzing Environmental Data. John Wiley & Sons: Chichester, U.K.
33. Portier CJ.1994. Biostatistical issues in the design and analysis of animal carcinogenicity experiments. Environmental Health Perspectives 102(Suppl. 1): 5-8.
34. R Development Core Team.2011. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing: Vienna, Austria. ISBN 3-900051-07-0.
35. Roy A, Guha N, Kopylev L, Spassova M, Fox J, White P.2012. Nonparametric Bayesian methods for benchmark dose estimation. Abstract - 2012 Joint Statistical Meetings, San Diego CA, http://www.amstat.org/meetings/jsm/2012/onlineprogram/AbstractDetails.cfm?abstractid=304373 [accessed 3 May 2012].
36. Schlosser PM, Lilly PD, Conolly RB, Janszen DB, Kimbell JS.2003. Benchmark dose risk assessment for formaldehyde using airflow modeling and a single-compartment, DNA-protein cross-link dosimetry model to estimate human equivalent doses. Risk Analysis 23: 473-487.
37. Stern AH. 2008. Environmental health risk assessment. In Encyclopedia of Quantitative Risk Analysis and Assessment, Vol.2, Melnick EL, Everitt BS (eds). John Wiley & Sons: Chichester, UK; 580-589.
38. Silvapulle MJ, Sen PK.2004. Constrained Statistical Inference: Order, Inequality, and Shape Constraints. John Wiley & Sons: Chichester, UK.
39. U.S. EPA. 2012. Benchmark Dose Technical Guidance Document. Technical Report number EPA/100/R-12/001, U.S. Environmental Protection Agency, Washington, DC.
40. West RW, Nitcheva DK, Piegorsch WW.2009. Bootstrap methods for simultaneous benchmark analysis with quantal response data. Environmental and Ecological Statistics 16: 63-73.
41. Wheeler MW, Bailer AJ.2008. Model averaging software for dichotomous dose response risk estimation. Journal of Statistical Software 26: Article Number 5.
42. Wheeler MW, Bailer AJ.2009. Comparing model averaging with other model selection strategies for benchmark dose estimation. Environmental and Ecological Statistics 16: 37-51.
43. Wheeler MW, Bailer AJ.2012. Monotonic Bayesian semiparametric benchmark dose analysis. Risk Analysis 32: 1207-1218.
44. Wright FT.1978. Estimating strictly increasing regression functions. Journal of the American Statistical Association 73: 636-639.
45. Xiong H. 2011. Nonparametric Statistical Approaches for Benchmark Dose Estimation in Quantitative Risk Assessment. PhD Thesis, Program in Applied Mathematics, University of Arizona, Tucson, AZ.
46. Yuan Y, Yin G.2011. Dose-response curve estimation: a semiparametric mixture approach. Biometrics 67: 1543-1554.
47. Zhao O, Woodroofe M.2012. Estimating a monotone trend. Statistica Sinica 22: 359-378.
48. Zhu Y, Wang T, Jelsovsky JZH.2007. Bootstrap estimation of benchmark doses and confidence limits with clustered quantal data. Risk Analysis 27: 447-465.