EconPapers    
Economics at your fingertips  
 

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

Anthony Y. C. Kuk

Journal of the Royal Statistical Society Series C, 2004, vol. 53, issue 2, 369-386

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.

Date: 2004
References: View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
https://doi.org/10.1046/j.1467-9876.2003.05369.x

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssc:v:53:y:2004:i:2:p:369-386

Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-9876

Access Statistics for this article

Journal of the Royal Statistical Society Series C is currently edited by R. Chandler and P. W. F. Smith

More articles in Journal of the Royal Statistical Society Series C from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().

 
Page updated 2025-03-19
Handle: RePEc:bla:jorssc:v:53:y:2004:i:2:p:369-386