The researchers developed a new method called VEIL to estimate variance components in a mixed linear model using Bayesian principles. They used the Gibbs sampler, a numerical technique, to analyze the variance components in the model. By applying this method to simulated data sets, they found that Gibbs sampling can accurately estimate the marginal distributions of variance components in the model.