Bayesian Causal Inference
Read the book
Workshops
Mailing list
Causal inference with panel data
14
Marketing Mix Modelling and Experimental Calibration
Preface
Foundations
Tools of Composition
1
Bayesian inference: optimisation and sampling
2
Causal quantities and g-computation
3
Causal thinking with graphs
4
Causal building blocks: forks, chains, and colliders
Causal inference with cross-sectional data
Composing Meaningful Models
5
Propensity Scores and Information Weighting
6
Supply, Demand and Instrumental Variables
7
Structural Equation Models and Path Diagrams
8
Discrete Choice Counterfactuals
9
Sensitivity Analysis: Model Checking and Theory Construction
Causal inference with panel data
Making the Counterfactual Explicit
10
Before and After: Change Scores to ANCOVA
11
Interrupted Time Series: No Control Group, Still Causal?
12
Synthetic Controls and Counterfactual Trajectories
13
Two-Way Fixed Effects: What Repeating Units Reveal
14
Marketing Mix Modelling and Experimental Calibration
Epilogue
References
Causal inference with panel data
14
Marketing Mix Modelling and Experimental Calibration
14
Marketing Mix Modelling and Experimental Calibration
GO BUY THE BOOK!
13
Two-Way Fixed Effects: What Repeating Units Reveal
Epilogue
