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Adjusting for mortality effects in chronic toxicity testing: Mixture model approach
Author(s) -
Wang Shin Cheng David,
Smith Eric P.
Publication year - 2000
Publication title -
environmental toxicology and chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 171
eISSN - 1552-8618
pISSN - 0730-7268
DOI - 10.1002/etc.5620190124
Subject(s) - ceriodaphnia dubia , poisson regression , statistics , toxicant , fecundity , confidence interval , regression analysis , regression , poisson distribution , chronic toxicity , econometrics , toxicology , mathematics , biology , toxicity , population , demography , medicine , acute toxicity , sociology
Chronic toxicity tests, such as the Ceriodaphnia dubia 7‐d test are typically analyzed using standard statistical methods such as analysis of variance or regression. Recent research has emphasized the use of Poisson regression or more generalized regression for the analysis of the fecundity data from these studies. A possible problem in using standard statistical techniques is that mortality may occur from toxicant effects as well as reduced fecundity. A mixture model that accounts for fecundity and mortality is proposed for the analysis of data arising from these studies. Inferences about key parameters in the model are discussed. A joint estimate of the inhibition concentration is proposed based on the model. Confidence interval estimation via the bootstrap method is discussed. An example is given for a study involving copper and mercury.