A simple model for extra-Binomial variability is the Beta-Binomial. A complication in testing the Binomial against the Beta-Binomial alternative is that the Binomial lies on the boundary of the Beta-Binomial, which forces modifications to the usual asymptotic arguments. In this paper, we propose a Bayesian test using a pair of approximate Bayes factors, one for the case in which the maximum likelihood estimator (MLE) of the extra-Binomial variability is zero and one for the case in which it is positive. These approximate Bayes factors are easy to compute. We evaluate the operating characteristics of the Bayes factors and find them to be more powerful than the likelihood ratio test. We then apply the method to three data sets, including one in which the issue is whether a logistic regression intercept should be considered a random effect. In each case, our approximate Bayes factors are close to the exact Bayes factors, which may also be computed with additional effort.
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