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Spatial Cluster Detection for Repeatedly Measured Outcomes while Accounting for Residential History


  • Andrea J. Cook,

    Corresponding author
    1. Group Health Research Institute, Seattle, WA 98101, USA
    2. Department of Biostatistics, University of Washington, Seattle, WA 98105, USA
    • Phone: +1-206-287-4257, Fax: +1-206-287-2871
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  • Diane R. Gold,

    1. The Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
    2. Department of Environmental Health, Harvard School of Public Health, Boston, MA 02115, USA
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  • Yi Li

    1. Department of Biostatistics, Harvard School of Public Health and the Dana Farber Cancer Institute, Boston, MA 02115, USA
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Spatial cluster detection has become an important methodology in quantifying the effect of hazardous exposures. Previous methods have focused on cross-sectional outcomes that are binary or continuous. There are virtually no spatial cluster detection methods proposed for longitudinal outcomes. This paper proposes a new spatial cluster detection method for repeated outcomes using cumulative geographic residuals. A major advantage of this method is its ability to readily incorporate information on study participants relocation, which most cluster detection statistics cannot. Application of these methods will be illustrated by the Home Allergens and Asthma prospective cohort study analyzing the relationship between environmental exposures and repeated measured outcome, occurrence of wheeze in the last 6 months, while taking into account mobile locations.