The odds ratio for a binary predictor indicates how much more likely a successful outcome is under one condition compared with another condition.
Dawid [ 12] rejects the counterfactual concept seemingly because, on it's own, it is not powerful enough to solve the fundamental problems of causal inference (e.g. in a fixed individual at a fixed time one can observe the outcome only under one condition).
Their results could not be seen as definitive, however, with total C storage predicted to be 0-90-9%gher under one climate model outcome, and 5-6% lower under another climate model outcome.
Prosecutors did, however, avoid a more disturbing outcome: Alex and Derek could have been convicted under one theory and Mr. Chavis under another, guaranteeing that someone who was innocent was convicted.
Secondly, findings were extracted from the primary sources into a spreadsheet and grouped under one of the outcome categories: barriers, facilitators, and perceptions/views of collaboration [ 35].
That is, it is about bringing the relevant causal factors under one's rational direction so as to achieve the desired outcome.
That's an outcome no one wants.
