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http://hdl.handle.net/1942/1969
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DC Field | Value | Language |
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dc.contributor.author | FAES, Christel | - |
dc.contributor.author | GEYS, Helena | - |
dc.contributor.author | AERTS, Marc | - |
dc.contributor.author | MOLENBERGHS, Geert | - |
dc.date.accessioned | 2007-11-09T15:17:10Z | - |
dc.date.available | 2007-11-09T15:17:10Z | - |
dc.date.issued | 2006 | - |
dc.identifier.citation | COMPUTATIONAL STATISTICS & DATA ANALYSIS, 51(3). p. 1848-1861 | - |
dc.identifier.issn | 0167-9473 | - |
dc.identifier.uri | http://hdl.handle.net/1942/1969 | - |
dc.description.abstract | Within the past decade, there has been an increasing interest in the problem of joint analysis of clustered multiple outcome data, motivated by developmental toxicity applications. Typically, a toxic insult early in gestation may result in a resorbed fetus or a fetal death. If however the fetus survives the entire gestation period, growth reduction such as low birth weight may occur, or can exhibit a malformation. Ideally, a model should take the complete hierarchical structure of the data into account. So far, however, one has tackled the challenges in this setting only partly each time making different restricting assumptions (e.g., restriction to viable fetuses only). In addition, because of genetic similarity and the same treatment conditions, offsprings of the same mother behave more alike than those of another mother. Thus, responses on different fetuses within a cluster are likely to be correlated. The ultimate scientific question requires assessing the full effect of dose administration, not only in the malformation and weight outcome, but also in the death outcome. A hierarchical Bayesian method is proposed to this effect. Such a model can serve as a basis for quantitative risk assessment. (c) 2005 Elsevier B.V. All rights reserved. | - |
dc.description.sponsorship | We gratefully acknowledge support from the Institute for the Promotion of Innovation by Science and Technology (IWT) in Flanders, Belgium, from the Fund for Scientific Research Flanders and from the IAP research network nr P5/24 of the Belgian Government (Belgian Science Policy). | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER SCIENCE BV | - |
dc.rights | (c) 2005 Elsevier B.V. All rights reserved. | - |
dc.subject.other | Bayesian methods; benchmark dose; hierarchical model; toxicology | - |
dc.subject.other | Bayesian methods; benchmark dose; hierarchical model; toxicology | - |
dc.title | A hierarchical modeling approach for risk assessment in developmental toxicity studies | - |
dc.type | Journal Contribution | - |
dc.identifier.epage | 1861 | - |
dc.identifier.issue | 3 | - |
dc.identifier.spage | 1848 | - |
dc.identifier.volume | 51 | - |
local.format.pages | 14 | - |
local.bibliographicCitation.jcat | A1 | - |
dc.description.notes | Hasselt Univ, Ctr Stat, B-3590 Diepenbeek, Belgium.Faes, C, Hasselt Univ, Ctr Stat, Agoralaan, B-3590 Diepenbeek, Belgium.christel.faes@uhasselt.be | - |
local.type.refereed | Refereed | - |
local.type.specified | Article | - |
dc.bibliographicCitation.oldjcat | A1 | - |
dc.identifier.doi | 10.1016/j.csda.2005.12.002 | - |
dc.identifier.isi | 000242704300030 | - |
item.accessRights | Restricted Access | - |
item.validation | ecoom 2008 | - |
item.fulltext | With Fulltext | - |
item.contributor | FAES, Christel | - |
item.contributor | GEYS, Helena | - |
item.contributor | AERTS, Marc | - |
item.contributor | MOLENBERGHS, Geert | - |
item.fullcitation | FAES, Christel; GEYS, Helena; AERTS, Marc & MOLENBERGHS, Geert (2006) A hierarchical modeling approach for risk assessment in developmental toxicity studies. In: COMPUTATIONAL STATISTICS & DATA ANALYSIS, 51(3). p. 1848-1861. | - |
crisitem.journal.issn | 0167-9473 | - |
crisitem.journal.eissn | 1872-7352 | - |
Appears in Collections: | Research publications |
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a.pdf Restricted Access | Published version | 411.89 kB | Adobe PDF | View/Open Request a copy |
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