Front Door Criterion: Adjustment Formula

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Causal Inference: Understanding Treatment Effects

Explores treatment effects, confounding variables, and challenges in interpreting observational study results.

Disentangling Confounding and Nonsense Associations

Explores statistical dependence, confounding, and causal inference methods, emphasizing the distinction between existing and new approaches.

Causal Analysis of Observational Data

Covers causal analysis of observational data, pitfalls, tools for valid conclusions, and addressing confounding variables.

Causal Inference: Estimands and Ontologies

Explores causal inference, emphasizing the importance of committing to an ontology for drawing causal inferences and selecting appropriate estimands.

Causal Effects Bounds: Sensitivity Parameters on Risk Difference Scale

Explores deriving bounds for causal effects using sensitivity parameters on the risk difference scale, addressing limitations and proposing new approaches.

Causal Inference & Directed Graphs

Explores causal inference, directed graphs, and fairness in algorithms, emphasizing conditional independence and the implications of DAGs.

Causal Inference in Cognitive Neuroscience

Explores the promises of causal inference in cognitive neuroscience using neurostimulation approaches to understand brain-behavior relationships.

Higher Education and Successful Marriage

Analyzes the causal effect of higher education on successful marriage and covers criteria for causal inference.

Model Selection and Local Geometry

Explores model selection challenges in causal models and the impact of local geometry on statistical inference.

Region of Convergence: Single Pole

Covers the concept of Region of Convergence for signals with single poles.