A set of training materials for professionals working in intervention epidemiology, public health microbiology and infection control and hospital hygiene.
We could debate whether or not we are able to 'measure' a causal effect. In my view, what we measure are observations (counts) expressed in numbers, rates, risks for example.
The comparison is already a computation, resulting in an 'effect', which caj be consided an estmation of the effect in the population.
If the effect (e.g. measure of association) is causal or not, cannot be measured, not tested. It can merely be inferred.
I think even when we take a survey and count, at the end the numbers obtained are only estimates,
and so more important to me is to what extend should an estimate be consider useful, in fact what are tolerable error margins, given that no 2 situations are truely comparable?
Perhaps we should open a philosophy wiki?