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Weighted logistic regression and robust analysis of diverse toxicology data
Authors:Douglas G Simpson  Raymond J Carroll  Minge Xie  Daniel J Guth
Institution:1. University of Illinois , Champaign, Illinois, 61820;2. Texas A&3. M University , College Station, Texas, 77843-3143;4. National Institute of Statistical Sciences , Research Triangle Park, North Carolina, 27709;5. U.S. Environmental Protection Agency , Research Triangle Park, North Carolina, 27711
Abstract:Simpson, Carroll, Zhou and Guth (1996) developed an ordinal response regression approach to meta-analysis of data from diverse toxicology studies, applying the methodology to a database of acute inhalation studies of tetra-chloroethylene. We present an alternative analysis of the same data, with two major differences: (1) interval censored scores are assigned worst-case values, e.g., a score known to be in the interval 0,1] is set equal to 1; and (2) the response is reduced to a binary response (adverse, nonadverse). We explore the stability of the analysis by varying a robustness parameter and graphing the curves traced out by the estimates and confidence intervals.
Keywords:binary response  combining information  environmental statistics  generalized estimating equation  toxicology
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