4 citations · 27 across the 12 of their papers we have counts for
7 papers · 1 filter
-GNF: A Copula-based Sensitivity Analysis to Unobserved Confounding Using Normalizing Flows
Sourabh Balgi, Jose M. Peña, Adel Daoud
We propose a novel sensitivity analysis to unobserved confounding in observational studies using copulas and normalizing flows. Using the idea of interventional equivalence of stru…
Image-based Treatment Effect Heterogeneity
Connor T. Jerzak, Fredrik Johansson, Adel Daoud
Randomized controlled trials (RCTs) are considered the gold standard for estimating the average treatment effect (ATE) of interventions. One use of RCTs is to study the causes of g…
Estimating Causal Effects Under Image Confounding Bias with an Application to Poverty in Africa
Connor T. Jerzak, Fredrik Johansson, Adel Daoud
Observational studies of causal effects require adjustment for confounding factors. In the tabular setting, where these factors are well-defined, separate random variables, the eff…
To What Extent Do Disadvantaged Neighborhoods Mediate Social Assistance Dependency? Evidence from Sweden
Cheng Lin, Adel Daoud, Maria Branden
Occasional social assistance prevents individuals from a range of social ills, particularly unemployment and poverty. It remains unclear, however, how and to what extent continued…
Conceptualizing Treatment Leakage in Text-based Causal Inference
Adel Daoud, Connor T. Jerzak, Richard Johansson
Causal inference methods that control for text-based confounders are becoming increasingly important in the social sciences and other disciplines where text is readily available. H…
Counterfactual Analysis of the Impact of the IMF Program on Child Poverty in the Global-South Region using Causal-Graphical Normalizing Flows
Sourabh Balgi, Jose M. Peña, Adel Daoud
This work demonstrates the application of a particular branch of causal inference and deep learning models: \emph{causal-Graphical Normalizing Flows (c-GNFs)}. In a recent contribu…