www.uhasselt.be
DSpace

Document Server@UHasselt >
Research >
Research publications >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/8189

Title: Statistical methods for developmental toxicity - Analysis of clustered multivariate binary data
Authors: Ryan, Louise
Molenberghs, Geert
Issue Date: 1999
Publisher: NEW YORK ACAD SCIENCES
Citation: UNCERTAINTY IN THE RISK ASSESSMENT OF ENVIRONMENTAL AND OCCUPATIONAL HAZARDS, 895. p. 196-211
Abstract: This paper discusses some of the statistical issues that arise from developmental toxicity studies, wherein pregnant mice are exposed to chemicals in order to assess possible adverse effects on developing Fetuses. We begin with a review of some current approaches to risk assessment, based on NOAELs, and provide justification for the use of methods based on dose-response models, Due to the hierarchical nature of the data, such models are more complicated in the present context than, say, in cancer studies. For example, multivariate binary outcomes arise when each fetus in a litter is assessed for the presence of malformations and/or tow birth weight. We describe a multivariate exponential family model that works well for these data and that is flexible in terms of allowing response rates to depend on cluster size. Maximum Likelihood estimation of model parameters and the construction of score tests for dose effect are briefly discussed. Results are illustrated with data from several NTP studies.
Notes: Harvard Univ, Sch Publ Hlth, Boston, MA 02115 USA. Dana Farber Canc Inst, Boston, MA 02115 USA. Limburgs Univ Ctr, Ctr Stat, B-3590 Diepenbeek, Belgium.Ryan, L, Harvard Univ, Sch Publ Hlth, 44 Binney St, Boston, MA 02115 USA.
URI: http://hdl.handle.net/1942/8189
ISI #: 000085328100014
ISSN: 0077-8923
Type: Journal Contribution
Validation: ecoom, 2001
Appears in Collections: Research publications

Files in This Item:

Description SizeFormat
Published version426.41 kBAdobe PDF

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.