In the context of a Gaussian multiple regression model, we address the problem of variable selection when in the list of potential predictors there are factors, that is, categorical variables. We adop
The 1st column shows whether the smaller or larger priors were used; the 3rd column shows the number of times (out of 7000 data sets) the true (i.e., the data-generating) model had the highest posteri
(a) random walk on age. (b) iid random effect for time. (c) random walk on time. (d) two-dimensional random walk for age-time interaction. Note: red dashed lines = priors; black solid lines = posterio
