Table of Contents

Getting Started

• Causal Reasoning with ChiRho

Tutorials

• Causal probabilistic programming without tears
  • Outline
  • Observation 1: causal models are probabilistic programs
  • Observation 2: causal uncertainty is probabilistic uncertainty
  • Observation 3: causal inference is probabilistic inference
  • Recap
  • A Causal Bayesian Workflow
  • References

Examples

• Backdoor adjustment
  • Outline
  • Setup
  • Overview: Systematically adjusting for observed confounding
  • Example: Evaluating the impact of a job training program
  • Causal Probabilistic Program
  • Causal Query: average treatment effect (ATE)
  • Causal Inference as Probabilistic Inference
  • Results
  • References
• Causal effect variational autoencoder
  • Outline
  • Setup
  • Overview: Proxy variables and latent confounders
  • Example: Synthetic Data
  • Causal Probabilistic Program
  • Causal Query: conditional average treatment effect (CATE)
  • Causal Inference as Probabilistic Inference
  • Results
  • References
• Deep structural causal model counterfactuals
  • Outline
  • Setup
  • Overview: Counterfactual estimation with normalizing flows
  • Example: Morpho-MNIST
  • Model: deep structural causal model
  • Causal Query: counterfactual data generation
  • References
• Structured latent confounders
  • Outline
  • Setup
  • Overview: Observational Causal Inference with Grouped Data
  • Example: Electric Company Education Study
  • Causal Probabilistic Program
  • Causal Query: average treatment effect (ATE)
  • Causal Inference as Probabilistic Inference
  • Results
  • References
• Mediation analysis and (in)direct effects
  • Outline
  • Setup
  • Overview: mediation analysis
  • Example: the effect of family interventions on future substance use
  • Causal Probabilistic Program
  • Causal Query: average natural direct effect (ANDE)
  • Causal Inference as Probabilistic Inference
  • Results
• Estimating causal effects using instrumental variables
  • Setup
  • Overview
  • Causal Probabilistic Program
  • Naive Estimator of the Causal Effect
  • Causal Query: Average Treatment Effect (ATE)
  • Causal Inference as Probabilistic Inference
  • Results
  • Conclusions and next steps
  • Further reading
• Estimating the causal effects of drug treatment on gene expression
  • Outline
  • Dev setup
  • Understanding the mechanism of action of a drug using causal inference
  • Goal: Understand the effects that the cancer drug candidate Pracinostat SB939 has on other target genes
  • Causal Probabilistic Program
  • Computing causal queries
  • References
• Causal effect estimation in panel data
  • Outline
  • Setup
  • Overview: Robust Causal Inference with Panel Data
  • Example: California Smoking Cessation
  • Causal Query: Counterfactual Prediction
  • Effect estimation with ordinary Bayesian inference
  • Robust effect estimation with modular Bayesian inference
  • References
• Doubly robust estimation with Chirho
  • Outline
  • Setup
  • Overview: Robust causal inference with cut modules
  • Example: Synthetic data generation from a high-dimensional generalized linear model
  • Effect estimation using cut modules
  • References
• Automated doubly robust estimation with ChiRho
  • Setup
  • Overview: automated robust estimation pipeline
  • Causal Probabilistic Program
  • Causal Query: Average treatment effect (ATE)
  • Results
  • References
• Causal reasoning in dynamical systems
  • Outline
  • Setup
  • Overview: Causal Inference in Continuous Time Dynamical Systems
  • Example: Assessing Intervention Strategies in an Epidemic Model
  • Causal Probabilistic Program
  • Probabilistic Inference over Dynamical System Parameters
  • Exploring Interventions
  • References
• Explainable reasoning with ChiRho (categorical variables)
  • Outline
  • Motivation
  • Setup
  • But-for Causal Explanations
  • Context-sensitive Causal Explanations
  • Probability of Causation and Responsibility
  • Further Discussion
• Actual Causality and the modified Halpern-Pearl definition
  • Intuitions and formalization
  • Implementation
  • Examples

Documentation

• Counterfactual
  • Operations
  • Handlers
  • Internals
• Interventional
  • Operations
  • Handlers
• Observational
  • Operations
  • Handlers
  • Internals
• Indexed
  • Operations
  • Handlers
  • Internals
• Dynamical
  • Types
  • Operations
  • Handlers
  • Internals
• Robust
  • Operations
  • Handlers
  • Internals
• Explainable
  • Operations
  • Handlers
  • Internals

For Contributors

• Contributing to ChiRho
  • Development
  • Dev Setup
  • Testing
  • Submitting
  • Code of conduct
• Design Notes
  • Introduction
  • Interventions
  • Counterfactual Semantics from Interventions and Possible Worlds
  • Sampling and Conditioning via Reparameterization
  • Causal Queries as Program Transformations
  • References

Indices and tables

• Index

• Module Index

• Search Page