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A review of spatial causal inference methods for environmental and epidemiological applications
[article]
2020
arXiv
pre-print
The scientific rigor and computational methods of causal inference have had great impacts on many disciplines, but have only recently begun to take hold in spatial applications. Spatial casual inference poses analytic challenges due to complex correlation structures and interference between the treatment at one location and the outcomes at others. In this paper, we review the current literature on spatial causal inference and identify areas of future work. We first discuss methods that exploit
arXiv:2007.02714v1
fatcat:ujag67wnabfk5i77ebn6fg6gfe