We use Demographic and Health Survey data to evaluate the impact of random spatial displacements on analyses that involve assigning covariate values from ancillary areal and point feature data. We introduce a method to determine the maximum probability covariate (MPC), and compare this to the naive covariate (NC) selection method with respect to obtaining the true covariate of interest. The MPC selection method outperforms the NC selection method by increasing the probability that the correct covariate is chosen. Proposed guidelines also address how characteristics of ancillary areal and point features contribute to uncertainty in covariate assignment.
