Spatial clustering of the failure to geocode and its implications for the detection of disease clustering.

@article{Zimmerman2008SpatialCO,
  title={Spatial clustering of the failure to geocode and its implications for the detection of disease clustering.},
  author={Dale L. Zimmerman and Xiangming Fang and Soumya Mazumdar},
  journal={Statistics in medicine},
  year={2008},
  volume={27 21},
  pages={
          4254-66
        }
}
Geocoding a study population as completely as possible is an important data assimilation component of many spatial epidemiologic studies. Unfortunately, complete geocoding is rare in practice. The failure of a substantial proportion of study subjects' addresses to geocode has consequences for spatial analyses, some of which are not yet fully understood. This article explicitly demonstrates that the failure to geocode can be spatially clustered, and it investigates the implications of this for… 
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Estimating spatial variation in disease risk from locations coarsened by incomplete geocoding
Reestimating a minimum acceptable geocoding hit rate for conducting a spatial analysis
TLDR
Results indicate that variations in intensity, clustering and aggregation levels lead to different minimum acceptable geocoding match rates, and specific techniques such as cluster detection seem to be especially sensitive to the existence of non-geocoded data, so the highly approved 85% geocoded rate may need to be raised.
Geographic variability in geocoding success for West Nile virus cases in South Dakota.
Minimum geocoding match rates: an international study of the impact of data and areal unit sizes
TLDR
An international investigation into the impact of the (in)ability to geocode an address on the resulting spatial pattern is conducted, finding that the level of geocoding success depends on the number of points and theNumber of areal units under analysis, but generally show that the necessary levels of geOCoding success are lower than found in previous research.
Local indicators of geocoding accuracy (LIGA): theory and application
TLDR
This paper finds that a family of curves describes the relationship between perturbability and positional error, and uses these curves to evaluate sensitivity of alternative spatial weight specifications to positional error both globally and locally.
A research agenda: does geocoding positional error matter in health GIS studies?
  • G. Jacquez
  • Medicine
    Spatial and spatio-temporal epidemiology
  • 2012
Geocoding Error, Spatial Uncertainty, and Implications for Exposure Assessment and Environmental Epidemiology
TLDR
Surfaces of spatial patterns in errors are developed in order to identify locations in the study area where exposures may be over-/under-estimated and methods for quantifying and interpreting geocoding error with respect to exposure misclassification are suggested.
Using Imputation to Provide Location Information for Nongeocoded Addresses
TLDR
This manuscript develops and evaluates a set of imputation strategies for dealing with missing spatial information from nongeocoded addresses and indicates that the imputation strategy based on using available population-based age, gender, and race information performed the best overall at the county, tract, and block group levels.
Evaluation of geoimputation strategies in a large case study
TLDR
Characteristics of the estimated records such as the demographic profile and population density information provide a measure of certainty of geographic imputation in geoimputation methods.
Uncertainty in Geospatial Health: Challenges and Opportunities Ahead.
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