4 citations · 4 across the 3 of their papers we have counts for
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What Should We Measure Next? Finding Identification Strategies by Refining Mechanisms
Mikko Väänänen, Fanyu Cui, Carlos Cinelli +1
Canonical approaches in causal inference treat model specification as fixed, assuming that researchers directly translate all relevant domain knowledge into a causal model, which c…
Omitted Variable Bias in Difference-in-Differences Designs
Juejue Wang, Pedro H. C. Sant'Anna, Victor Chernozhukov +1
We study the omitted variable bias (OVB) problem in canonical difference-in-differences (DiD) designs when unobserved confounding induces departures from the parallel trends assump…
Causally Sound Priors for Binary Experiments
Nicholas J. Irons, Carlos Cinelli
We introduce the BREASE framework for the Bayesian analysis of randomized controlled trials with a binary treatment and a binary outcome. Approaching the problem from a causal infe…