Weighted logistic regression and robust analysis of diverse toxicology data

Douglas G. Simpson, Minge Xie, Raymond J. Carroll, Daniel J. Guth

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

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 tetrachloroethylene. 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.

Original languageEnglish (US)
Pages (from-to)2615-2632
Number of pages18
JournalCommunications in Statistics - Theory and Methods
Volume25
Issue number11
DOIs
StatePublished - 1996
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Statistics and Probability

Keywords

  • Binary response
  • Combining information
  • Environmental statistics
  • Generalized estimating equation
  • Toxicology

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