9 citations · 59 across the 32 of their papers we have counts for
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stat.ME2019★ 3 cited
Identifiability of causal effects with multiple causes and a binary outcome
Dehan Kong, Shu Yang, Linbo Wang
Unobserved confounding presents a major threat to causal inference from observational studies. Recently, several authors suggest that this problem may be overcome in a shared confo…
stat.ME2019★ 1 cited
Multiplicative Effect Modeling: The General Case
Jiaqi Yin, Sonia Markes, Thomas S. Richardson +1
Generalized linear models, such as logistic regression, are widely used to model the association between a treatment and a binary outcome as a function of baseline covariates. Howe…