Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/2228
Title: Modeling combined continuous and ordinal outcomes in a clustered setting
Authors: FAES, Christel 
GEYS, Helena 
AERTS, Marc 
MOLENBERGHS, Geert 
CATALANO, Paul 
Issue Date: 2004
Publisher: AMER STATISTICAL ASSOC & INTERNATIONAL BIOMETRIC SOC
Source: JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS, 9(4). p. 515-530
Abstract: Measurements of both continuous and categorical outcomes appear in many statistical problems. One such example is the study of teratology and developmental toxicity, where both the probability that a live fetus is malformed (ordinal) or of low birth weight (continuous) are important measures in the context of teratogenicity. Although multivariate methods of the analysis of continuous outcomes are well understood. methods for jointly continuous and discrete outcomes are less familiar. We propose a likelihood-based method that is an extension of the Plackett-Dale approach. Specification of the full likelihood will be avoided using pseudo-likelihood methodology. The estimation of safe dose levels as part of quantitative risk assessment will be illustrated based on a developmental toxicity experiment of diethylene glycol dimethyl ether in mice.
Notes: Limburgs Univ Ctr, Ctr Stat, Diepenbeek, Belgium. Harvard Univ, Sch Publ Hlth, Dept Biostat Sci, Dana Farber Canc Inst, Boston, MA 02115 USA. Harvard Univ, Sch Publ Hlth, Dept Biostat, Boston, MA 02115 USA.Faes, C, Limburgs Univ Ctr, Ctr Stat, Univ Campus, Diepenbeek, Belgium.christel.faes@luc.ac.be
Keywords: benchmark dosed; clustering; Plackett-Dale model; pseudo-likelihood; quantitative risk assessment;benchmark dose; clustering; Plackett-Dale model; pseudo-likelihood; quantitative risk assessment
Document URI: http://hdl.handle.net/1942/2228
ISSN: 1085-7117
e-ISSN: 1537-2693
DOI: 10.1198/108571104X16349
ISI #: 000225913100007
Rights: (c) 2004 American Statistical Association and the International Biometric Society
Category: A1
Type: Journal Contribution
Validations: ecoom 2006
Appears in Collections:Research publications

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