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A Shared Response Model for Clustered Binary Data in Developmental Toxicity Studies

A shared response model for clustered binary data in developmental toxicity studies
Authors: Pang, Z.; Kuk, A.Y.C.;

A Shared Response Model for Clustered Binary Data in Developmental Toxicity Studies

Abstract

SummaryExisting distributions for modeling fetal response data in developmental toxicology such as the beta‐binomial distribution have a tendency of inflating the probability of no malformed fetuses, and hence understating the risk of having at least one malformed fetus within a litter. As opposed to a shared probability extra‐binomial model, we advocate a shared response model that allows a random number of fetuses within the same litter to share a common response. An explicit formula is given for the probability function and graphical plots suggest that it does not suffer from the problem of assigning too much probability to the event of no malformed fetuses. The EM algorithm can be used to estimate the model parameters. Results of a simulation study show that the EM estimates are nearly unbiased and the associated confidence intervals based on the usual standard error estimates have coverage close to the nominal level. Simulation results also suggest that the shared response model estimates of the marginal malformation probabilities are robust to misspecification of the distributional form, but not so for the estimates of intralitter correlation and the litter‐level probability of having at least one malformed fetus. The proposed model is fitted to a set of data from the U.S. National Toxicology Program. For the same dose–response relationship, the fit based on the shared response distribution is superior to that based on the beta‐binomial, and comparable to that based on the recently proposedq‐power distribution (Kuk, 2004,Applied Statistics53,369–386). An advantage of the shared response model over theq‐power distribution is that it is more interpretable and can be extended more easily to the multivariate case. To illustrate this, a bivariate shared response model is fitted to fetal response data involving visceral and skeletal malformation.

Country
Singapore
Keywords

dose-response function, Models, Biological, Bone and Bones, Applications of statistics to biology and medical sciences; meta analysis, Xenobiotics, Dose-response function, Fetal Development, Mice, Medical applications (general), Pregnancy, Toxicity Tests, odds ratio, Animals, Computer Simulation, EM algorithm, Risk assessment, Models, Statistical, Dose-Response Relationship, Drug, 2,4,5-Trichlorophenoxyacetic Acid, Herbicides, risk assessment, Estimation in survival analysis and censored data, Odds ratio, exchangeability, Developmental toxicity data, 004, developmental toxicity data, Intracluster correlation, intra-cluster correlation, Viscera, Exchangeability, Female

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Average
Average
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