Much of the data used in social science is aggregated into spatial units, even if the analysis itself does not explicitly incorporate that information. A key concern with such aggregation, however, is that changes in the units of aggregation themselves cause difficulty in comparing data gathered on the old boundaries and the new boundaries. Such changes present serious concerns to researchers who may exclude observations or cases due to a lack of comparable units or omit certain key variables. While geographers have long examined this problem and created methods of projecting data from one spatial unit into another, known as areal interpolation, it is telling that a recent article notes the difficulty for researchers in implementing even the most basic solutions without relying heavily on programming skills or proprietary software.
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