The unlikelihood effect: When knowing more creates the perception of less
Quantifying causality in data science with quasi-experiments
Developing improved observational methods for evaluating therapeutic effectiveness
The causal foundations of applied probability and statistics
When causation does not imply correlation: robust violations of the Faithfulness axiom
Interpolating Causal Mechanisms: The Paradox of Knowing More
The Fallacy Of The Null-Hypothesis Statistical-Significance Test