Adjustment for unmeasured confounding through informative priors for the confounder-outcome relation.

As incorporating (informative) prior information for the confounder-outcome relation may reduce the bias due to unmeasured confounding, we consider this approach one of many possible sensitivity analyses of unmeasured confounding.