Bipartite Causal Inference with Interference
نویسندگان
چکیده
منابع مشابه
Causal Inference with Interference
LAN LIU: Causal Inference with Interference (Under the direction of Dr. Michael G. Hudgens) Recently, increasing attention has focused on making causal inference when interference is possible, i.e., when the potential outcomes of one individual may be affected by the treatment (or exposure) of other individuals. For example, in infectious diseases, whether one individual becomes infected may de...
متن کاملToward Causal Inference With Interference.
A fundamental assumption usually made in causal inference is that of no interference between individuals (or units); that is, the potential outcomes of one individual are assumed to be unaffected by the treatment assignment of other individuals. However, in many settings, this assumption obviously does not hold. For example, in the dependent happenings of infectious diseases, whether one person...
متن کاملCausal Inference for Binary Data with Interference
Joseph Rigdon: Causal Inference for Binary Data with Interference (Under the direction of Michael Hudgens) Developing methods to quantify the effects of interventions to prevent infectious diseases in the presence of interference is the overall objective of this research. Interference is present when an individual’s outcome is affected by the treatment of any other individuals under study. Firs...
متن کاملCausal Inference with Counterfactuals
Note we are not asking whether aspirin cures headaches in some more general sense, we wish to know whether this specific headache went away because of the decision to take aspirin. The only sensible way to answer this sort of question in the case of a specific event is to compare the outcome which you observed with the counterfactual outcome which you would have observed if you had chosen not t...
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ژورنال
عنوان ژورنال: Statistical Science
سال: 2021
ISSN: 0883-4237
DOI: 10.1214/19-sts749