1.88 × 10−10, respectively, to give a Bayes factor of 0.074. Hence the data are 14 times more likely under the saturated model. The probability of the data under the single f model is 1.36 × 10−10 so that the data are 10 times more likely under this model when compared to the recessive (HWE) model, but slightly less likely than under the saturated model. The normalizing constant under the single f model was evaluated using importance sampling Monte Carlo, with sampling from both the prior, and from a four-dimensional normal (as described in Section 3.1), both being computationally feasible for these data.
