Assessing the effect of an influenza vaccine in an encouragement design.

By Keisuke Hirano, Guido W. Imbens, Donald B. Rubin, Xiao‐Hua Zhou. 2000

414 citations recorded by the source corpus.

Subfields: Health, Modeling and Simulation, Statistics and Probability

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Citations in the corpus

Causal Inference through a Witness Protection Program (2014, neutral): “Richardson et al. (2011) and Hirano et al. (2000) provide further discussion.”
Instrumental Variables Estimation in Political Science: A Readers’ Guide (2011, background): “Well-known examples of this type of design are randomly assigned encouragements of patients to get a flu vaccination (Hirano et al. 2000) or randomly assigned attempts by canvassers to mobilize voters on the eve of an election (Gerber and Green 2000).”
A Likelihood-Based Analysis for Relaxing the Exclusion Restriction in Randomized Experiments with Imperfect Compliance (2013, methodology): “This approach, however, does not easily apply to cases where, contrary to the Hirano et al. (2000) paper, the identifiability conditions are satisfied given the wellrecognized problems arising with the Bayesian approach in the context of mixture models (McLachlan and Peel, 2000).”
Exploiting multiple outcomes in Bayesian principal stratification analysis with application to the evaluation of a job training program (2013, background): “For example, covariates generally improve inference on causal effects by enhancing the prediction of missing intermediate and final potential outcomes [e.g., Hirano et al. (2000), Gilbert and Hudgens (2008)].”
Effects of a Voluntary Summer Reading Intervention on Reading Achievement: Results From a Randomized Field Trial (2006, background): “Formally, the evaluation of the present intervention is a randomized encouragement design (Hirano et al., 2000), which provides the causal effect of assignment to the treatment rather than receipt of the treatment.”
Tutorial in Biostatistics: Instrumental Variable Methods for Causal Inference* (2014, methodology): “where the quantities on the left-hand and right-hand sides of (5) other than b can be estimated as discussed in Section 4 and [58, 60, 64].”
On Instrumental Variables Estimation of Causal Odds Ratios (2011, background): “…the IV level z of exposure x (Tan, 2010), odds{Y (x) = 1|X(z) = x} odds{Y (0) = 1|X(z) = x} ,(2) and to so-called local or principal stratification causal odds ratios (Hirano et al., 2000; Frangakis and Ru- bin 2002; Abadie, 2003; Clarke andWindmeyer, 2009; see Bowden et al., 2010, for a review).”
Transparent Parametrizations of Models for Potential Outcomes (2012, methodology): “We consider the influenza vaccine data from McDonald et al. (1992), which was previously analyzed by Hirano et al. (2000); see Table 5.”