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Critical Values and Power for a Small
Sample Test of Difference in by John S. Lawson and Benjamin Ahlstrom Journal of Data Science, v.4, no.3, 357-370 Abstract We develop a likelihood ratio test statistic, based on the beta-binomial
distribution, for comparing a single treated group with dichotomous data
to dual control groups. This statistic is useful in cases where there
is overdispersion or extra-binomial variation. We apply the statistic
to data from a two year rodent carcinogenicity study with dual control
groups. The test statistic we developed is similar to others that have
been developed for incorporation of historical control groups with rodent
carcinogenicity experiments. However, for the small sample case we considered,
large sample theory used by the other test statistics did not apply. We
determined the critical values of this statistic by enumerating its distribution.
A small Monte Carlo study shows the new test statistic controls the significance
level much better than Fisher's exact test when there is overdispersion
and that it has adequate power. Homepage | Table of Contents | Full Text of This Article
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