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Spat Demogr. 2016 Jul;4(2):155-173. Epub 2015 Jun 23.

Influence of Demographic and Health Survey Point Displacements on Distance-Based Analyses.

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


We evaluate the impacts of random spatial displacements on analyses that involve distance measures from displaced Demographic and Health Survey (DHS) clusters to nearest ancillary point or line features, such as health resources or roads. We use simulation and case studies to address the effects of this introduced error, and propose use of regression calibration (RC) to reduce its impact. Results suggest that RC outperforms analyses involving naive distance-based covariate assignments by reducing the bias and MSE of the main estimator in most settings. Proposed guidelines also address the effect of the spatial density of destination features on observed bias.

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