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Activity Number:
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393
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Type:
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Invited
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Date/Time:
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Thursday, August 15, 2002 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Survey Research Methods*
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| Abstract - #300291 |
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Title:
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Modeling Multivariate Data with a Common Spatial Factor
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Author(s):
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Melanie Wall*+
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Affiliation(s):
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University of Minnesota
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Address:
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MMC 303 Mayo 8303, 420 Delaware St., SE, Minneapolis, Minnesota, 55455-0392,
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Keywords:
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Abstract:
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There are usually two kinds of correlations in multivariate spatially referenced data: correlations between variables measured at the same locations, and correlations of each variable across the locations. We hypothesize that these two kinds of correlations both are caused by a single spatially correlated underlying factor. Under this hypothesis, a spatial factor model is developed under a normal assumption for the data, and the parameters are estimated with the maximum likelihood method. Our main goal is to predict the underlying factor at observed locations, as well as locations where no data are observed, and provide a map which may be used to identify the spatial trends or clusters of high and low values of the underlying factor. The model is applied to a collection of several different county-level, disease-specific mortality rates in Minnesota to find whether there exists a common spatially varying factor underlying the diseases throughout the state.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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