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Activity Number: 493
Type: Contributed
Date/Time: Wednesday, August 3, 2016 : 8:30 AM to 10:20 AM
Sponsor: Section on Risk Analysis
Abstract #318922
Title: Modeling Survival and Growth Outcomes in a Toxicology Study
Author(s): Jing Zhang* and A. John Bailer and James T. Oris and Scott E. Belangerz
Companies: and Miami University and Miami University and Procter & Gamble
Keywords: Relative inhibition ; Bayesian ; Zero-inflated ; Multivariate
Abstract:

Toxicants in aquatic organisms may impact a variety of responses including hatching, survival, growth and reproduction. These responses have a hierarchical relationship, i.e. survival is only possible for hatched organisms and growth measurements are only available if organisms survive. Linear models and generalized linear models have been widely used to analyze individual responses separately; however, an analysis that simultaneously considers the structure of multiple responses would allow a more comprehensive assessment of toxicity. Motivated by a study of hatching-survival-growth in fish, a simultaneous modeling approach is developed. In the present study, we propose a Bayesian multivariate modeling approach to analyze the hierarchical toxicity responses simultaneously and estimate the concentrations associated with a specified level of relative inhibition (RIp) on hatching-survival success and growth (weight and length).


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