Casuality aka causation & association

Casuality aka causation & association

1. Non-casual associations

   • 1. Chance associations that can occur at random
   • 2. Artifactual associations that occur through some error or defect in the design or execution of a study.
   • 3. Indirect associations in which an exposure is associated with an outcome but through a confounding variable.

2. have ruled out the likelihood of any of these non-causal explanations for an apparent association

   • one is left with one additional possibility: The association is causal.
     • can finally accept the evidence from a research article you need to check if the researchers have discussed their significant results in terms of causality.

3. presence of an association between A and B does not tell you anything at all about:

   • a) The presence of the causality
   • b) The direction of causality.

4. “To show that A has caused B (rather than B causing A, or A and B both being caused by C [a confounder]), you need more than a correlation coefficient” (….or a RR)6. Bradford Hill “tests for causation” are outlined in the box below (