Statistical dose-response models with hormetic effects

Human and Ecological Risk Assessment (HERA)

Volumn 7, Issue 4, 2001, Pages 891-908

  Schabenberger, Oliver ^a   Birch, Jeffrey B ^a  

^a VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY   (United States)

Author keywords

Bias; Localized estimation; Nonlinear regression; Nonparametric regression; Switching functions

Indexed keywords

EID: 26444608015     PISSN: 10807039     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (22)

1. Brain P and Cousens R. 1989. An equation to describe dose responses where there is stimulation of growth at low doses. Weed Research 29:93-6
2. Calabrese EJ and Baldwin LA. 1998. Hormesis as a default parameter in RfD derivation. Belle Newsletter 7(1):13-6
3. Crump K. 2001. Evaluating the Evidence for Hormesis: A Statistical Perspective. Human Ecol Risk Assess (this issue)
4. Fan J and Gijbels I. 1996. Monographs on Statistics and Applied Probability 66, Local Polynomial Modeling and Its Applications. Chapman and Hall, London, UK
5. Gregoire TG and Schabenberger O. 1996a. A non-linear mixed-effects model to predict cumulative bole volume of standing trees. J Appl Statistics 23 (2&3:) 257-71
6. Gregoire TG and Schabenberger O. 1996b. Nonlinear mixed-effects modeling of cumulative bole volume with spatially correlated within-tree data. J Agricult, Biolog, Environ Statistics 1:107-19
7. Härdle W. 1990. Applied Nonparametric Regression. Econometric Study Monographs. Cambridge University Press, Cambridge, MA, USA
8. Hsiao AI, Liu SH, and Quick WA. 1996. Effect of ammonium sulfate on the phytotoxicity, foliar uptake, and translocation of imazamethabenz in wild oat. J Plant Growth Regul 15:115-20
9. Laerke PE and Streibig JC. 1995. Foliar absorption of some glyphosate formulations and their efficacy on plants. Pesticide Science 44:107-16
10. Morgan PH, Mercer LP, and Flodin NW. 1975. General model for nutritional responses of higher organisms. In: Proceedings of the National Academy of Science, USA, 72:4327-31
11. Myers WR, Myers RH, Carter HJr, and Kimber LJr. 1996. Two-state designs for the logistic regression model in single-agent bioassays. J Biopharmaceutical Statistics 6:283-301
12. Nottingham QJ and Birch JB. 2000. A semiparametric approach to analysing dose-response data. Statistics in Medicine 19:389-404
13. Nottingham QJ, Birch JB, and Bodt BB. 2000. Local logistic regression: An application to Army penetration data. J Stat Comput Simul 66:35-50
14. Sandral GA, Dear BS, Pratley JE, et al. 1997. Herbicide dose rate response curves in subterranean clover determined by a bioassay. Australian J Experimental Agriculture 37:67-74
15. Schabenberger O, Tharp BE, Kells JJ, and Penner D. 1999. Statistical tests for hormesis and effective dosages in herbicide dose response. Agronomy J 91(4):713-21
16. Seefeldt SS, Jensen JE, and Fuerst P. 1995. Log-logistic analysis of herbicide dose-response relationships. Weed Technology 9:218-27
17. Streibig JC. 1980. Models for Curve-fitting Herbicide Dose Response Data. Acta Agriculturae Scandinavica 30: 59-63
18. Streibig JC. 1981. A method for determining the biological effect of herbicide mixtures. Weed Science 29:469-73
19. Swinton SM and Lyford CP. 1996. A test for choice between hyperbolic and sigmoidal models for crop yield response to weed density. J Agricult, Biolog, and Environ Statistics 1:97-106
20. Thornley JHM and Johnson IR. 1990. Plant and Crop Models. Clarendon Press, Oxford, UK
21. UNSCEAR 1958. Report of the United Nations Scientific Committee on the Effects of Atomic Radiation. Official Records of the General Assembly, 13th Session, Supplement No 17. United Nations, NY, NY, USA
22. Valentine HT and Gregoire TG. 2001. A switching model of bole taper. Canadian J Forest Res (to appear)