Intuitive Causation

Forecasting for COVID19 has Failed

June, 2020

DSA ADS Course - 2021

Forecasting, COVID19, John Ioannidis, Public Policy, Health Policy, Causal Inference, Forensic Medicine, Causality, Intuitive Causation, Probabilistic Causation

Forecasting is usually impossible in high causal density environments. Scenario planning with applied probability and adaptation to near real-time data is optimal strategy. Epidemic forecasting is usually a fools errand yet appropriate analysis of experience and historical precedent is helpful.

Review of Causal Inference in Forensic Medicine

March, 2020

DSA ADS Course - 2021

Causal Inference, Forensic Medicine, Causality, Intuitive Causation, Probabilistic Causation

Causality - intuitive causation vs. probabilistic causation. Probabilistic causation is optimal yet discuss other techniques to seek true causation. Sometimes true causation is impossible to find and discuss optimal strategy under such circumstances.

Abstract

Causes of Effects and Effects of Causes

2014

Abstract

This paper summarizes methods that were found useful in estimating the probability that one event was a necessary cause of another, as interpreted by law makers. We show that the fusion of observational and experimental data can yield informative bounds which, under certain circumstances, meet legal criteria of causation. We further investigate the circumstances under which such bounds can emerge, and the philosophical dilemma associated with determining individual cases from statistical data.