Ned English
NORC at the University of Chicago, Chicago
Ned English is a Senior Survey Methodoligist at NORC at the University of Chicago, where he has been since 2002. His expertise lies in the interface between GIS (geographic information systems) and survey methodology, and so has been involved in research including address-based sampling (ABS), targeting rare populations, and the implimentation of the USPS delivery-sequence file (DSF) over the past ten years. Ned has a Master's degree in Geography from the University of Wisconsin-Madison and a Bachelor's degree in Geography from McGill University.![IconGems-Print](images/IconGems-Print.png)
356 – Contributed Poster Presentations: Survey Research Methods Section
Challenges in Linking Demographic Data at Different Geographic Levels
Adrijo Chakraborty
NORC at the University of Chicago
Rebecca Curtis
NORC at the University of Chicago
Ned English
NORC at the University of Chicago, Chicago
Ilana Ventura
NORC at the University of Chicago
Edward J. Mulrow
NORC at the University of Chicago
Researchers can be challenged by data sets published at incongruent levels of aggregation. However, there exists the need to combine such data while maintaining its integrity and geographic relationships. We explore two approaches with trade-offs in accuracy and efficiency, with a focus on ZIP codes and US Census tracts. Our first method uses geographic information systems (GIS) to weight tract-level data from the American Community Survey (ACS) based on spatial overlap. The weights are the percent of area overlap for each tract intersecting each ZIP code. This method avoids the duplication of data caused by allocating all of a tract's data to each ZIP code it intersects and allows for a more nuanced distribution of data over matching the tract centroid to the ZIP code. Secondly, we describe a framework that uses calibration techniques to estimate overlapping regions based on published margin totals. The overlap proportion is used to allocate a portion of each tract to the ZIP code. Exploratory analysis provides insight into the strengths and weaknesses of each approach.