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dc.contributor.authorGuan, Yawen
dc.contributor.authorPage, Garritt L.
dc.contributor.authorReich, Brian J
dc.contributor.authorVentrucci, Massimo
dc.contributor.authorYang, Shu
dc.date.accessioned2020-12-28T13:21:24Z
dc.date.available2020-12-28T13:21:24Z
dc.date.issued2020-12-22
dc.identifier.urihttp://hdl.handle.net/10754/666727
dc.description.abstractAdjusting for an unmeasured confounder is generally an intractable problem, but in the spatial setting it may be possible under certain conditions. In this paper, we derive necessary conditions on the coherence between the treatment variable of interest and the unmeasured confounder that ensure the causal effect of the treatment is estimable. We specify our model and assumptions in the spectral domain to allow for different degrees of confounding at different spatial resolutions. The key assumption that ensures identifiability is that confounding present at global scales dissipates at local scales. We show that this assumption in the spectral domain is equivalent to adjusting for global-scale confounding in the spatial domain by adding a spatially smoothed version of the treatment variable to the mean of the response variable. Within this general framework, we propose a sequence of confounder adjustment methods that range from parametric adjustments based on the Matern coherence function to more robust semi-parametric methods that use smoothing splines. These ideas are applied to areal and geostatistical data for both simulated and real datasets
dc.description.sponsorshipThis work was partially supported by the National Institutes of Health (R01ES031651-01,R01ES027892-01) and King Abdullah University of Science and Technology (3800.2).
dc.publisherarXiv
dc.relation.urlhttps://arxiv.org/pdf/2012.11767
dc.rightsArchived with thanks to arXiv
dc.titleA spectral adjustment for spatial confounding
dc.typePreprint
dc.eprint.versionPre-print
dc.contributor.institutionUniversity of Nebraska - Lincoln.
dc.contributor.institutionBrigham Young University.
dc.contributor.institutionNorth Carolina State University.
dc.contributor.institutionUniversity of Bologna.
dc.identifier.arxivid2012.11767
refterms.dateFOA2020-12-28T13:22:01Z


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