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Strategies for robust designs in toxicological tests
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NSTL
Elsevier
Toxicological tests are widely used to study toxicity in aquatic environments. Reproduction is a possible endpoint of this type of experiment, whose response variable is given by counts. There is a literature on the most suitable probability distribution to be used for analyzing the data. In the theory of optimal experimental design, the assumption of this probability distribution is essential, and when this assumption is not appropriate, there may be a loss of efficiency in the design obtained. The main objective of this study is to propose robust designs when there is uncertainty about the probability distribution of the response variable. Three different strategies for attaining this goal are introduced and compared, and they are then applied to toxicological tests based on Ceriodaphnia dubia and Lemna minor. In addition, a simulation study is performed to test the estimation properties of the robust designs obtained.
Elemental information matrixExponential family distributionLinear logistic modelD-optimalityElemental information matrixExponential family distributionLinear logistic modelD-optimalityTOXICITYVARIABLESHORMESISTOOL
NSTL
Elsevier
