Toronto Data Workshop - Emily Riederer On Causality From Observational Data

Toronto Data Workshop - Emily Riederer on causality from observational data

Rohan Alexander

Better data testing with the data (error) generating process move(data) - Emily Riederer

Emily Riederer @ Capital One | Explicit design at the start of a project | Data Science Hangout

1.5 - Causation in Observational Studies

Brady Neal - Causal Inference

Varonis Data Risk Assessment Explained | How Varonis' Data Risk Assessment (DRA) Works

Somerford Associates

tidycf Turning analysis on its head by turning cashflows on their sides – Emily Riederer

What's in your Workflow?

Causal Data Science -- Elias Bareinboim (@ 1st Workshop on Interactive Causal Learning)

Toronto Data Workshop - DoSS toolkit launch

Rohan Alexander

“Drawing Causality from Observational Data in Healthcare:..."

OHSU Informatics

Some Thoughts on Causal Inference with Observational Data

Advances in Algorithmic Recourse: Ensuring Causal Consistency, Fairness, & Robustness

Toronto Machine Learning Series (TMLS)

“Applying causal inference to real-world data”

OHSU Informatics

2024 Quantitative Workshop 05 - Exploratory analysis and visualization, Part 2

Operationalizing Column-Name Contracts with dbtplyr (w/ Emily Riederer)

dbt

Observational Studies - Causal Inference

Data Ready Part 6: Correlation, Causation & Misleading Data

Georgia State University Library

Looking at Additional Results in Giant Tables: Causal Inference Bootcamp

Mod•U: Powerful Concepts in Social Science

Less casual causal inference for experiments and longitudinal data: Research talk by Julia Rohrer

Dr. Tobias Dienlin