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Abstract:
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Interest in and availability of social network data has led to increasing attempts to make causal and statistical inferences using data collected from subjects linked by social network ties. But inference about all kinds of estimands, starting with simple sample means, is challenging when only a single network of non-independent observations is available. There is a dearth of principled methods for dealing with the dependence that such observations can manifest. We describe methods for causal and semiparametric inference when the dependence is due solely to the transmission of information or outcomes along network ties.
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