4 citations · 4 across the 9 of their papers we have counts for
10 papers
Partitioning Time in Target Trial Emulation
Harold Tankpinou Zoumenou, Simon Ferreira, Charles Assaad +6
In target trial emulation, the treatment strategies that patients follow are inferred from the treatments they actually receive in routine care. However, in most settings, the outc…
Time Partitioning in Target Trial Emulation
Harold Tankpinou Zoumenou, Simon Ferreira, Charles Assaad +3
In target trial emulation, time partitioning enables researchers to handle time-varying confounders and immortal time bias with appropriate methods. Based on two clinical scenarios…
On Efficient Adjustment for Micro Causal Effects in Summary Causal Graphs
Isabela Belciug, Simon Ferreira, Charles K. Assaad
Observational studies in fields such as epidemiology often rely on covariate adjustment to estimate causal effects. Classical graphical criteria, like the back-door criterion and t…
Identifying Macro Causal Effects in C-DMGs over DMGs
Simon Ferreira, Charles K. Assaad
The do-calculus is a sound and complete tool for identifying causal effects in acyclic directed mixed graphs (ADMGs) induced by structural causal models (SCMs). However, in many re…
Identifying Macro Causal Effects in a C-DMG over ADMGs
Simon Ferreira, Charles K. Assaad
Causal effect identification using causal graphs is a fundamental challenge in causal inference. While extensive research has been conducted in this area, most existing methods ass…
Retrieving Classes of Causal Orders with Inconsistent Knowledge Bases
Federico Baldo, Simon Ferreira, Charles K. Assaad
Traditional causal discovery methods often depend on strong, untestable assumptions, making them unreliable in real-world applications. In this context, Large Language Models (LLMs…
Average Controlled and Average Natural Micro Direct Effects in Summary Causal Graphs
Simon Ferreira, Charles K. Assaad
In this paper, we investigate the identifiability of average controlled direct effects and average natural direct effects in causal systems represented by summary causal graphs, wh…
Identifying Macro Conditional Independencies and Macro Total Effects in Summary Causal Graphs with Latent Confounding
Simon Ferreira, Charles K. Assaad
Understanding causal relations in dynamic systems is essential in epidemiology. While causal inference methods have been extensively studied, they often rely on fully specified cau…
Case Studies of Causal Discovery from IT Monitoring Time Series
Ali Aït-Bachir, Charles K. Assaad, Christophe de Bignicourt +5
Information technology (IT) systems are vital for modern businesses, handling data storage, communication, and process automation. Monitoring these systems is crucial for their pro…
Identifiability of Direct Effects from Summary Causal Graphs
Simon Ferreira, Charles K. Assaad
Dynamic structural causal models (SCMs) are a powerful framework for reasoning in dynamic systems about direct effects which measure how a change in one variable affects another va…