title: A modified Bonferroni method for discrete data.
abstract: The Bonferroni adjustment for multiple comparisons is a simple and useful method of controlling the overall false positive error rate when several significance tests are performed in the evaluation of an experiment. In situations with categorical data, the test statistics have discrete distributions. The discreteness of the null distributions can be exploited to reduce the number of significance tests taken into account in the Bonferroni procedure. This reduction is accomplished by using only the information contained in the marginal totals.
authors.affiliation: Biostatistics Branch, National Cancer Institute, Bethesda, Maryland 20892.
authors.forename: R E
authors.initials: RE
authors.lastname: Tarone
mesh_terms: D000818:Animals; D001699:Biometry / Q000379:methods*; D015197:Carcinogenicity Tests / Q000706:statistics & numerical data; D005189:False Positive Reactions; D015203:Reproducibility of Results