| Re: Mapping Z-scores [message #2527 is a reply to message #2519] |
Mon, 07 July 2014 15:48  |
Thea-DHS
Messages: 28
Registered: March 2013
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The DHS Program is currently writing a new report in the Spatial Analysis Report series that will outline some of the key considerations when interpolating Demographic and Health Survey data. There will be an announcement on The DHS Program website once the final version is released. In the meantime, we'd like to make you aware of some guidelines, and direct you to the two most recent Spatial Analysis Report publications, which will help you to understand the displacement of The DHS Program GPS datasets, and how to account for the displacement in your analysis:
The DHS Program strongly recommends using sampling weights whenever you use DHS data in analysis, including when interpolating the spatial data.
It is possible to create interpolated layers of DHS indicators using cluster-level estimates and there are numerous published studies that have done this. However, it is important when interpreting the results of such analyses, or conducting your own analysis, to take into account the fact that most DHS surveys are not designed to be representative below the level of the DHS regions (to view or download the DHS regions for Malawi surveys, please visit http://spatialdata.dhsprogram.com/boundaries.html?country=MW). Therefore, interpolating the cluster level data or using it to conduct small area estimation will introduce error into your study. Inverse Distance Weighting and other univariate methods of interpolation do not yield any error or uncertainty estimates. Alternatively, multi-variate methods are capable of producing measurements of error alongside the interpolated indicator estimates.
If this has not answered your question adequately, please reply.
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