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


With this paper we explore the sensitivity of study results to spatial displacements associated with Demographic and Health Survey (DHS) data in research that integrates ancillary raster data. Through simulation studies, we found that the impact of DHS point displacements on raster-based analyses can be moderated through the generation of covariates representing average values from neighborhood buffers. Additionally, raster surface characteristics (i.e., spatial smoothness) were found to affect the extent of bias introduced through point displacements. Although simple point extraction produced unbiased estimates in analyses involving smooth continuous surfaces, it is not recommended in analyses that involve categorical raster surfaces.

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This research was supported in part by grants from the National Institute of Environmental Health Sciences (T32ES007018, P30ES010126) and the United States Agency for International Develop-ment (USAID) through the MEASURE DHS project (Contract No. GPO-C-00-08-00008-00).

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The authors declare that they have no competing interests.

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Correspondence to Carolina Perez-Heydrich.

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Appendix A: Appendix A corresponds to a.txt file containing the R code used to simulate the point displacement procedure. (TXT 7 kb)


Appendix B: In order to determine the level of smoothness, i.e., spatial autocorrelation coefficient, of an ancillary raster dataset, investigators can run the following R function, which calls the raster dataset as its sole argument. (TXT 1 kb)


Appendix C: Appendix C is an R function that returns a vector of misclassification probabilities for all locations, and an estimate of the resulting misclassification rate of a given categorical raster surface. (TXT 1 kb)


Appendix D: Appendix D contains figures of all categorical raster surfaces that were used in simulation studies, and the relationship between estimated bias and misclassification rate of simulated surfaces. (PDF 357 kb)

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Perez-Heydrich, C., Warren, J.L., Burgert, C.R. et al. Influence of Demographic and Health Survey Point Displacements on Raster-Based Analyses. Spat Demogr 4, 135–153 (2016).

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  • Locational error
  • Spatial analysis
  • Covariate misclassification