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Abstract Details
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Activity Number:
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184
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Type:
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Contributed
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Date/Time:
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Monday, August 1, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics and the Environment
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| Abstract - #300924 |
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Title:
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Conditional Maximum Likelihood Estimation of Spatial Variation in Disease Risk from Locations Subject to Geocoding Errors
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Author(s):
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Dale Zimmerman*+
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Companies:
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University of Iowa
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Address:
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2141 Brown Deer Rd, Coralville, IA, 52241,
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Keywords:
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Case-control data ;
Geocode ;
Positional accuracy ;
Relative risk ;
Spatial epidemiology
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Abstract:
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The accurate assignment of geocodes to the residences of subjects in a study population is an important component of the data acquisition/assimilation stage of many spatial environmental epidemiological investigations. Unfortunately, it is not a simple matter to obtain accurate point-level geocodes. Ignoring the positional errors in geocoded data may lead to biased estimators of spatial variation in disease risk. In this talk, we modify Diggle and Rowlingson's (1994) conditional maximum likelihood estimation procedure for spatial variation in disease risk from locations ascertained without positional error, so as to permit valid inferences to be made from locations observed with error. The performance of the modified method relative to the original is investigated by simulation, allowing us to address the question of how large the positional errors must be for the modified method to be worth the additional level of complexity.
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Authors who are presenting talks have a * after their name.
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