Toward Causal Inference With Interference

By Michael G. Hudgens, E. Halloran. 2008

881 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Statistics and Probability

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Citations in the corpus

The Econometrics of Randomized Experiments (2016, methodology): “Athey, Eckles and Imbens (2015) introduce the notion of an articifial experiment.”
Efficient Policy Learning (2017, neutral): “For a discussion of treatment effect estimation under intereference, see Hudgens and Halloran (2008), Manski (2013), Sobel (2006), and references therein.”
Social Networks and Causal Inference (2013, background): “Formal statistical inference in this setting can however be challenging (Hudgens and Halloran 2008; Tchetgen Tchetgen and VanderWeele 2012).”
Design and Analysis of Experiments in Networks: Reducing Bias from Interference (2014, background): “arXiv: 1404.7530”
Matching methods for causal inference: A review and a look forward (2010, background): “Recent work has also begun thinking about how to relax this assumption in analyses (Hong and Raudenbush, 2006; Sobel, 2006; Hudgens and Halloran, 2008).”
Estimating Average Causal Effects Under Interference Between Units (2013, neutral): “9 The richness of these data makes Add Health a canonical dataset for methodological research related to social networks, as with Bramoulle et al. (2009), Chung et al. (2008), Goel and Salganik (2010), Goodreau et al. (2009), Goodreau (2007), Handcock et al. (2007), and Hunter et al. (2008).”
Large sample randomization inference of causal effects in the presence of interference (2014, methodology): “In this paper, the large sample distributions of the causal effect estimators proposed by Hudgens and Halloran (2008) are derived for two stage randomization studies.”
Tutorial in Biostatistics: Instrumental Variable Methods for Causal Inference* (2014, background): “The no-interference assumption is also not appropriate for situations such as estimating the effect of a vaccine on an individual because a non-vaccinated individualAmay benefit from individual B receiving the vaccine because A can no longer become infected from contact with person B [91].”
Causal Inference Under Multiple Versions of Treatment (2013, neutral): “The extension of the potential outcomes framework to address interference and spillover effects has been of use in a variety of substantive contexts [15, 16, 18, 19, 20].”
Estimating Direct and Indirect Effects of Foreign Direct Investment on Firm Productivity in the Presence of Interactions between Firms (2014, methodology): “Following, Hudgens and Halloran (2008) our approach to take into account the role of interactions among firms when evaluating the effects of foreign ownership on firms’ productivity is to use the proportion of foreign firms within well-defined clusters at the”
Identification and Estimation of Spillover Effects in Randomized Experiments (2017, background): “Hudgens and Halloran (2008) discuss unbiased estimation and variance calculations under partial interference under two-stage randomization designs.”
Detecting Spillover Effects: Design and Analysis of Multilevel Experiments (2012, methodology): “Building on the recent literature discussing the iden tification of causal effects in the presence of interference between units (Hudgens and Halloran 2008), our ap proach is to gauge spillover effects using a multilevel experimental design.”
Policy Learning With Observational Data (2017, neutral): “For a discussion of treatment effect estimation under intereference, see Hudgens and Halloran (2008), Manski (2013), and references therein.”
On causal inference in the presence of interference (2010, background): “Hudgens and Halloran6 also establish analogous conditions under which equality holds for each of the other Equations (11)–(13).”
Causal inference with misspecified exposure mappings: separating definitions and assumptions (2021, background): “Aronow and Samii (2017) recognize that the key methodological tool in Hudgens and Halloran (2008) was a terse description of the treatments assigned to all units.”