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It is often said that the fundamental problem of causal inference is a missing data problem -- the comparison of responses to two hypothetical treatment assignments is made difficult because for every experimental unit only one potential response is observed.
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Comment on inference for semiparametric models: Some questions and an answer, by PJ Bickel and J. Kwon
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Identifiability of normal and normal mixture models with nonignorable missing data
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