NSF-sponsored research on deep interactions

As part of our series on recent NSF-funded political science research, Rick Wilson points to . . . Yair Ghitza and Andrew Gelman. (Forthcoming). “Deep Interactions with MRP: Election Turnout and Voting Patterns Among Small Electoral Groups.” AJPS [DOI: 10.1111/ajps.12004].

Rick writes:

Accurately measuring attributes of the American public is critical to the success of government and society. This includes polls that allow lawmakers to understand their constituents’ preferences to inform their policy choices. It is also indispensible for government to accurately measure unemployment or the population itself through the Census. Yet conducting and analyzing surveys is an increasingly difficult proposition, with the growing abundance of cell-phone-only populations, the difficulty in reaching certain segments of the population, and many other challenges. New measurement techniques need to be developed for the 21st century.

This research demonstrates that standard survey analysis methods are often unstable and unsuitable for estimating values for small populations. In turn the article introduces a statistical method that combines survey and Census information that overcomes these problems. This particular research focuses on vote preferences, but the method can be applied generally to survey analysis, and as such is valuable for any person or organization with an interest in accurately measuring aspects of the American public.

This work should be viewed as a statistical innovation driven by an interdisciplinary approach to research. In a world where “big data” are becoming increasingly available, there is a temptation to think that standard statistical and computational methods can be arbitrarily pointed at large piles of data to make sense of the world; this thinking implies that funding should only go to the hard STEM disciplines, which are traditionally better trained at handling these quantitative tasks. This research demonstrates that standard data-crunching approaches often miss important structures, or can be entirely inappropriate for the question being asked. The research makes clear that scientific progress is achieved through collaboration across disciplines, such as between technical experts such as statisticians and computer scientists, and domain-specific experts such as political scientists, education policy experts, medical researchers and the like.

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