skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Integrating Data Across Misaligned Spatial Units
Abstract Theoretical units of interest often do not align with the spatial units at which data are available. This problem is pervasive in political science, particularly in subnational empirical research that requires integrating data across incompatible geographic units (e.g., administrative areas, electoral constituencies, and grid cells). Overcoming this challenge requires researchers not only to align the scale of empirical and theoretical units, but also to understand the consequences of this change of support for measurement error and statistical inference. We show how the accuracy of transformed values and the estimation of regression coefficients depend on the degree of nesting (i.e., whether units fall completely and neatly inside each other) and on the relative scale of source and destination units (i.e., aggregation, disaggregation, and hybrid). We introduce simple, nonparametric measures of relative nesting and scale, asex anteindicators of spatial transformation complexity and error susceptibility. Using election data and Monte Carlo simulations, we show that these measures are strongly predictive of transformation quality across multiple change-of-support methods. We propose several validation procedures and provide open-source software to make transformation options more accessible, customizable, and intuitive.  more » « less
Award ID(s):
1925693
PAR ID:
10480871
Author(s) / Creator(s):
; ; ;
Publisher / Repository:
Cambridge University Press
Date Published:
Journal Name:
Political Analysis
Volume:
32
Issue:
1
ISSN:
1047-1987
Page Range / eLocation ID:
17 to 33
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ; (, ACM/IMS Transactions on Data Science)
    null (Ed.)
    We develop GeoMatch as a novel, scalable, and efficient big-data pipeline for large-scale map matching on Apache Spark. GeoMatch improves existing spatial big-data solutions by utilizing a novel spatial partitioning scheme inspired by Hilbert space-filling curves. Thanks to its partitioning scheme, GeoMatch can effectively balance operations across different processing units and achieve significant performance gains. GeoMatch also incorporates a dynamically adjustable error-correction technique that provides robustness against positioning errors. We demonstrate the effectiveness of GeoMatch through rigorous and extensive empirical benchmarks that consider large-scale urban spatial datasets ranging from 166,253 to 3.78B location measurements. We separately assess execution performance and accuracy of map matching and develop a benchmark framework for evaluating large-scale map matching. Results of our evaluation show up to 27.25-fold performance improvements compared to previous works while achieving better processing accuracy than current solutions. We also showcase the practical potential of GeoMatch with two urban management applications. GeoMatch and our benchmark framework are open-source. 
    more » « less
  2. ; ; (, Journal of Geophysical Research: Oceans)
    Abstract We develop idealized analytical and numerical models to study how storm surge amplitudes vary within frictional, weakly convergent, nonreflective estuaries. Friction is treated using Chebyshev polynomials. Storm surge is represented as the sum of two sinusoidal components, and a third constituent represents the semidiurnal tide (D2). An empirical fit of storm surge shows that two sinusoidal components adequately represent storm surge above a baseline value (R2 = 0.97). We find that the spatial transformation of surge amplitudes depends on the depth of the estuary, and characteristics of the surge wave including time scale, amplitude, asymmetry, and surge‐tide relative phase. Analytical model results indicate that surge amplitude decays more slowly (largere‐folding) in a deeper channel for all surge time scales (12–72 hr). Deepening of an estuary results in larger surge amplitudes. Sensitivity studies show that surges with larger primary amplitudes (or shorter time scales) damp faster than those with smaller amplitudes (or larger time scales). Moreover, results imply that there is a location with maximum sensitivity to altered depth, offshore surge amplitude, and time scale and that the location of observed maximum change in surge amplitude along an estuary of simple form moves upstream when depth is increased. Further, the relative phase of surge to tide and surge asymmetry can change the spatial location of maximum change in surge. The largest change due to increased depth occurs for a large surge with a short time scale. The results suggest that both sea level rise and channel deepening may also alter surge amplitudes. 
    more » « less
  3. ; ; ; ; ; ; ; ; ; ; et al (, Ambio)
    Abstract Transformation toward a sustainable future requires an earth stewardship approach to shift society from its current goal of increasing material wealth to a vision of sustaining built, natural, human, and social capital—equitably distributed across society, within and among nations. Widespread concern about earth’s current trajectory and support for actions that would foster more sustainable pathways suggests potential social tipping points in public demand for an earth stewardship vision. Here, we draw on empirical studies and theory to show that movement toward a stewardship vision can be facilitated by changes in either policy incentives or social norms. Our novel contribution is to point out that both norms and incentives must change and can do so interactively. This can be facilitated through leverage points and complementarities across policy areas, based on values, system design, and agency. Potential catalysts include novel democratic institutions and engagement of non-governmental actors, such as businesses, civic leaders, and social movements as agents for redistribution of power. Because no single intervention will transform the world, a key challenge is to align actions to be synergistic, persistent, and scalable. 
    more » « less
  4. ; ; (, Behavior Research Methods)
    Abstract Adaptive design optimization (ADO) is a state-of-the-art technique for experimental design (Cavagnaro et al., 2010). ADO dynamically identifies stimuli that, in expectation, yield the most information about a hypothetical construct of interest (e.g., parameters of a cognitive model). To calculate this expectation, ADO leverages the modeler’s existing knowledge, specified in the form of a prior distribution.Informativepriors align with the distribution of the focal construct in the participant population. This alignment is assumed by ADO’s internal assessment of expected information gain. If the prior is insteadmisinformative, i.e., does not align with the participant population, ADO’s estimates of expected information gain could be inaccurate. In many cases, the true distribution that characterizes the participant population is unknown, and experimenters rely on heuristics in their choice of prior and without an understanding of how this choice affects ADO’s behavior. Our work introduces a mathematical framework that facilitates investigation of the consequences of the choice of prior distribution on the efficiency of experiments designed using ADO. Through theoretical and empirical results, we show that, in the context ofprior misinformation, measures of expected information gain are distinct from the correctness of the corresponding inference. Through a series of simulation experiments, we show that, in the case of parameter estimation, ADO nevertheless outperforms other design methods. Conversely, in the case of model selection, misinformative priors can lead inference to favor the wrong model, and rather than mitigating this pitfall, ADO exacerbates it. 
    more » « less
  5. ; ; ; (, Ecology and Evolution)
    ABSTRACT Anthropogenic change is reshaping the regulation and stability of animal population dynamics across broad biogeographic gradients. For example, abiotic and biotic interactions can cause gradients in population cycle period and amplitude, but this research is mostly constrained to small mammals. Caribou and reindeer (Rangifer tarandusspp.) are threatened by human‐caused change and are known to fluctuate in population over multidecadal scales. But it is unclear how ecological mechanisms drive these cycles and whether these mechanisms are similar to those found in smaller mammals. Here, we carried out a global biogeographic study ofRangiferpopulation cycles in response to top‐down and bottom‐up mechanisms. We hypothesized that predation and food resources would interact to affect the amplitude and period of population cycles across the species' range. To test this, we used a two‐pronged approach: (1) we conducted a range‐wide statistical analysis of population data from 43Rangiferherds; and (2) we built tri‐trophic mechanistic population models of predator–Rangifer–food interactions. This approach allowed us to merge theoretical and empirical approaches to better understand the drivers of population cycling across space and time. We found statistical evidence for long‐term cyclicity in 19Rangiferpopulations, and some evidence that decreasing food productivity and winter temperatures may have caused increased period length and amplitude across spatial gradients. Our mechanistic model largely agreed with our empirical results, showing that decreased food resources and increased predation can drive more intense cycles over time. These paired empirical and theoretical results suggest that gradients inRangiferpopulation cycles match ecological mechanisms found in smaller mammals. Moreover, human‐caused shifts in climate, food resources, and predators may shiftRangiferpopulation dynamics towards more booms and busts, threatening population persistence. We recommend that dynamic management strategies, in tandem with theoretical and empirical approaches, could be used to better understand and manage population cycles across space and time. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email