Volume 53, Issue 2

A litter‐based approach to risk assessment in developmental toxicity studies via a power family of completely monotone functions

Anthony Y. C. Kuk

National University of Singapore, Singapore

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First published: 19 March 2004
Citations: 9
Anthony Y. C. Kuk, Department of Statistics and Applied Probability, National University of Singapore, 3 Science Drive 2, 129790 Singapore.
E‐mail: stakuka@nus.edu.sg

Abstract

Summary. A new class of distributions for exchangeable binary data is proposed that originates from modelling the joint success probabilities of all orders by a power family of completely monotone functions. The distribution proposed allows flexible modelling of the dose–response relationship for both the marginal response probability and the pairwise odds ratio and is especially well suited for a litter‐based approach to risk assessment. Specifically, the risk of at least one adverse response within a litter takes on a simple form under the distribution proposed and can be reduced further to a generalized linear model if a complementary log–log‐link function is used. Existing distributions such as the beta–binomial or folded logistic functions have a tendency to assign too much probability to zero, leading to an underestimation of the risk that at least one foetus is affected and an overestimation of the safe dose. The distribution proposed does not suffer from this problem. With the aid of symbolic differentiation, the distribution proposed can be fitted easily and quickly via the method of scoring. The usefulness of the class of distributions proposed and its superiority over existing distributions are demonstrated in a series of examples involving developmental toxicology and teratology data.

Number of times cited according to CrossRef: 9

  • binomialRF: interpretable combinatoric efficiency of random forests to identify biomarker interactions, BMC Bioinformatics, 10.1186/s12859-020-03718-9, 21, 1, (2020).
  • Maximum Likelihood Estimation of Titer via a Power Family of Four-Parameter Logistic Model, Journal of Biopharmaceutical Statistics, 10.1080/10543406.2017.1333996, 28, 3, (492-500), (2017).
  • Likelihood estimation for exchangeable multinomial data, Communications in Statistics - Theory and Methods, 10.1080/03610926.2015.1053934, 46, 6, (2882-2892), (2016).
  • Markov counting models for correlated binary responses, Biostatistics, 10.1093/biostatistics/kxv006, 16, 3, (427-440), (2015).
  • Statistical evaluation of toxicological bioassays – a review, Toxicol. Res., 10.1039/C4TX00047A, 3, 6, (418-432), (2014).
  • Some properties of completely monotonic sequences and related interpolation, Applied Mathematics and Computation, 10.1016/j.amc.2012.11.073, 219, 10, (4958-4962), (2013).
  • A certain class of completely monotonic sequences, Advances in Difference Equations, 10.1186/1687-1847-2013-294, 2013, 1, (2013).
  • Circulating trophoblastic cells provide genetic diagnosis in 63 fetuses at risk for cystic fibrosis or spinal muscular atrophy, Reproductive BioMedicine Online, 10.1016/j.rbmo.2012.08.002, 25, 5, (508-520), (2012).
  • Modeling overdispersion with the normalized tempered stable distribution, Computational Statistics & Data Analysis, 10.1016/j.csda.2011.01.016, 55, 7, (2288-2301), (2011).