Statistical models for genetic susceptibility in toxicological and epidemiological investigations

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Models are presented for use in assessing genetic susceptibility to cancer (or other diseases) with animal or human data. Observations are assumed to be in the form of proportions, hence a binomial sampling distribution is considered. Generalized linear models are employed to model the response as a function of the genetic component; these include logistic and complementary log forms. Susceptibility is measured via odds ratios of response. relative to a background genetic group. Significance tests and confidence intervals for these odds ratios are based on maximum likelihood estimates of the regression parameters. Additional consideration is given to the problem of gene-environment interactions and to testing whether certain genetic identifiers/categories may be collapsed into a smaller set of categories. The collapsibility hypothesis provides an example of a mechanistic context wherein nonhierarchical models for the linear predictor can sometimes make sense.

Original languageEnglish (US)
Pages (from-to)77-82
Number of pages6
JournalEnvironmental Health Perspectives
Volume102
Issue numberSUPPL. 1
StatePublished - 1994
Externally publishedYes

Fingerprint

Statistical Models
Genetic Predisposition to Disease
Toxicology
Linear Models
Odds Ratio
Binomial Distribution
Likelihood Functions
Gene-Environment Interaction
Animal Diseases
Confidence Intervals
confidence interval
Maximum likelihood
Logistics
cancer
logistics
Neoplasms
Animals
Genes
Sampling
gene

ASJC Scopus subject areas

  • Environmental Science(all)
  • Environmental Chemistry
  • Public Health, Environmental and Occupational Health

Cite this

Statistical models for genetic susceptibility in toxicological and epidemiological investigations. / Piegorsch, Walter W.

In: Environmental Health Perspectives, Vol. 102, No. SUPPL. 1, 1994, p. 77-82.

Research output: Contribution to journalArticle

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