317 citations · 496 across the 18 of their papers we have counts for
5 papers · 1 filter
Complete Causal Identification from Ancestral Graphs under Selection Bias
Leihao Chen, Joris M. Mooij
Many causal discovery algorithms, including the celebrated FCI algorithm, output a Partial Ancestral Graph (PAG). PAGs serve as an abstract graphical representation of the underlyi…
Testing Partially-Identifiable Causal Queries Using Ternary Tests
Sourbh Bhadane, Joris M. Mooij, Philip Boeken +1
We consider hypothesis testing of binary causal queries using observational data. Since the mapping of causal models to the observational distribution that they induce is not one-t…
Can we detect treatment effect waning from time-to-event data?
Eni Musta, Joris Mooij
Understanding how the causal effect of a treatment evolves over time, including the potential for waning, is important for informed decisions on treatment discontinuation or repeti…
Revisiting the Berkeley Admissions data: Statistical Tests for Causal Hypotheses
Sourbh Bhadane, Joris M. Mooij, Philip Boeken +1
Reasoning about fairness through correlation-based notions is rife with pitfalls. The 1973 University of California, Berkeley graduate school admissions case from Bickel et. al. (1…
Foundations of Structural Causal Models with Latent Selection
Leihao Chen, Onno Zoeter, Joris M. Mooij
Three distinct phenomena complicate statistical causal analysis: latent common causes, causal cycles, and latent selection. Foundational works on Structural Causal Models (SCMs), e…