Estimating brood-specific reproductive inhibition potency in aquatic toxicity testing

Environmetrics

Volumn 23, Issue 8, 2012, Pages 696-705

  Zhang, Jing ^a   John Bailer, A ^a   Oris, James T ^a  

^a MIAMI UNIVERSITY   (United States)

Author keywords

Bayesian hierarchical models; Ceriodaphnia dubia; Multivariate; Reproductive toxicology

Indexed keywords

AQUATIC ORGANISM; EFFLUENT; ESTIMATION METHOD; GROWTH RESPONSE; INHIBITION; MORTALITY; MULTIVARIATE ANALYSIS; NUMERICAL MODEL; REPRODUCTION; TOXICITY TEST; TOXICOLOGY;

CERIODAPHNIA DUBIA;

EID: 84871674362     PISSN: 11804009     EISSN: 1099095X     Source Type: Journal    
DOI: 10.1002/env.2181     Document Type: Article

References (27)

1. Bailer AJ, Oris JT. 1993. Modeling reproductive toxicity in Ceriodaphnia tests. Environmental Toxicology and Chemistry 12: 787-791.
2. Bailer AJ, Oris JT. 1994. Assessing toxicity of pollutants in aquatic systems. In Case Studies in Biometry, Lange N, Ryan L, Billard L, Brillinger D, Conquest L, Greenhouse J (eds). Wiley: New York, NY; 25-40.
3. Bailer AJ, Oris JT. 1997. Estimating inhibition concentrations for different response scales using generalized linear models. Environmental Toxicology and Chemistry 16: 1554-1559.
4. Bailer AJ, Hughes MR, Denton DL, Oris JT. 2000. An empirical comparison of effective concentration estimators for evaluating aquatic toxicity test responses. Environmental Toxicology and Chemistry 19: 141-150.
5. Barata C, Fernandez-San Juan M, Feo ML, Eljarrat E, Soares A, Barcelo D, Baird D. 2012. Population growth rate responses of Ceriodaphnia dubia to ternary mixtures of specific acting chemicals: Pharmacological versus eco-toxicological modes of action. Environmental Science & Technology 46: 9663-9672.
6. Brooks S, Gelman A. 1998. General methods for monitoring convergence of iterative simulations. Journal of Computational and Graphical Statistics 7: 434-455.
7. Cameron AC, Johansson P. 1997. Count data regression using series expansions: with applications. Journal of Applied Econometrics 12: 203-223.
8. Chib S, Winkelmann R. 2001. Markov chain Monte Carlo analysis of correlated count data. Journal of Business and Economic Statistics 19: 428-435.
9. Delgado MA. 1992. Semiparametric generalized least squares in the multivariate nonlinear regression model. Economic Theory 8: 203-222.
10. Gelman A. 2006. Prior distributions for variance parameters in hierarchical models. Bayesian Analysis 1: 515-533.
11. Gurmu S, Elder J. 2000. Generalized bivariate count data regression models. Economics Letters 68: 31-36.
12. Johnson NL, Kotz S. 1969. Distributions in Statistics: Discrete Distributions. Houghton Mifflin: Boston.
13. Liang KY, Zeger SL. 1986. Longitudinal data analysis using generalized linear models. Biometrika 73: 13-22.
14. Ma J, Kockelman KM, Damien P. 2008. A multivariate Poisson-lognormal regression model for prediction of crash counts by severity, using Bayesian methods. Accident Analysis and Prevention 40: 964-975.
15. Mardia KV, Kent JT, Bibby JM. 1979. Multivariate Analysis. Academic Press: London.
16. Marshall AW, Olkin I. 1990. Multivariate distributions generated from mixtures of convolution and product families. In Topics in Statistical Dependence, Block HA, Sampson AR, Savits TH (eds). IMS Lecture Notes, Monograph Series. Institute of Mathematical Statistics: Hayward, CA; Vol 16: 371-393.
17. O'Hagan A, Forster JJ. 2004. Bayesian Inference, (2nd edn), Vol. 2B of Kendall's Advanced Theory of Statistics. Arnold: London.
18. Olkin I. 1994. Multivariate non-normal distributions and models of dependency. In Multivariate Analysis and its Application, Anderson TW, Fang KT, Olkin I (eds), Lecture Notes, Monograph Series. Institute of Mathematical Statistics: Hayward, CA; Vol 24: 37-53.
19. R Development Core Team. 2008. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing: Vienna, Austria. ISBN 3-900051-07-0, http://www.R-project.org.
20. Roex EWM, Van Gestel CAM, Van Wezel AP, Van Straalen NM. 2000. Ratios between acute aquatic toxicology and effects on population growth rates in relation to toxicant mode of action. Environmental Toxicology and Chemistry 19: 685-693.
21. Sturtz S, Ligges U, Gelman A. 2005. R2WinBUGS: a package for running WinBUGS from R. Journal of Statistical Software 12: 1-16.
22. Wang SC. (1998).Analysis of zero-heavy data using a mixture model approach. Ph.D. Dissertation, Virginia Polytechnic Institute and State University, Blacksburg.
23. Wang SC, Smith EP. 2000. Adjusting for morality effects in chronic toxicity testing: mixture model approach. Environmental Toxicology and Chemistry 19: 204-209.
24. Weber CI, Peltier WH, Norberg-King TJ, Horning WB, Kessler FA, Menkedick JR, Neiheisel TW, Lewis PA, Kemm K, Pickering QH, Robinson EL, Lazorchack JM, Wymer LJ, Freyberg RW. 1989.Short-Term Methods for Estimating the Chronic Toxicity of Effluents and Receiving Waters to Freshwater Organisms, (2nd edn). U.S. Environmental Protection Agency: Cincinnati, OH, EPA/600/4-89/001A.
25. Wheeler MW, Bailer AJ. 2009. Benchmark dose estimation incorporating multiple data sources. Risk Analysis 29: 249-256.
26. Zhang J, Bailer AJ, Oris JT. 2012a. Bayesian approach to estimating reproductive inhibition potency in aquatic toxicity testing. Environmental Toxicology and Chemistry 31: 916-927.
27. Zhang J, Bailer A J, Oris J T. 2012b. Bayesian potency estimation in aquatic toxicity testing when a toxicant affects both fecundity and survival of organisms. Environmental Toxicology and Chemistry 31: 1920-1930.