The mysteries multiply as we look through the literature but some answers are still forthcoming.

The mystery continues, leading us down an algorithmic path filled with broken sticks.

A parameter collapses, a sophisticated model looms afoot and we find the start of a trail of clues in this unexpected mystery.

An overview of two of the main obstacles to causal inference: Confounding and Selection Bias

An overview of the conditions required for instrumental variables and an example application in the built environment

A motivation and illustration of some of the basic principles underlying Causal Inference