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Spat Demogr. 2016 Jul;4(2):117-133. Epub 2015 Jun 20.

Influence of Demographic and Health Survey Point Displacements on Point-in-Polygon Analyses.

Author information

1
Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, CT, USA.
2
Department of Biological Sciences, Meredith College, Raleigh, NC, USA.
3
ICF International, Rockville, MD, USA.
4
Department of Geography, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

Abstract

We use Demographic and Health Survey (DHS) 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.

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