p Value Adjustments for Multiple Tests in Multivariate Binomial Models

Abstract Data from rodent carcinogenicity (preclinical) and clinical studies involving new drugs may be modeled as having come from multivariate binomial distributions. In two-year rodent carcinogenicity studies, there are typically 20–50 tissues examined for occurrence of any of several possible lesions. For a particular treatment group, the number of occurrences of a particular lesion at a particular tissue may be modeled as binomial, and the vector of such frequencies may be considered multivariate binomial with unspecified dependence structure. The same model may also apply to clinical side-effects data; in this case the marginal frequencies may represent occurrences of events ranging from headaches to ingrown toenails. Frequently, the goal of such studies is to isolate site-specific significant differences between treatment and control groups. For example, in rodent carcinogenicity analyses it is generally not sufficient to claim that a new compound causes an increase in tumors at some unspecified si...

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