Proving Causation Why do you think it was me?!

Causation A “correlation” between two variables does not immediately mean that one variable “causes” the other. The relationship is often influenced by other variables “lurking” in the background.

How to see causation?? The best evidence for causation comes from randomized comparative experiments. Why? The relationship may be due to direct causation, common response, or confounding.

Direct Causation There is a strong correlation between smoking cigarettes and death from lung cancer. Does smoking cigarettes cause lung cancer? There is a strong correlation between the availability of hand guns in America and the homicide rate. Is the availability of hand guns the cause of the homicide rate?

Does watching TV make you live longer? This is called a “nonsense” correlation. People with TV’s are also in more developed countries, have better health care, etc.

Common Response If “watching too much television” is the explanatory variable and “obesity in children” is the response variable, a possible lurking variable can be “poor food choices”. Did poor food choices cause obesity in children? Did poor food choices make children watch too much television (junk food in front of TV)?

Confounding You just don’t know if it was the explanatory variable or the lurking variable which caused the response variable. There is an association between variables, but you don’t know if there is a cause and effect relationship.

How they look… The arrows represent a cause-and-effect link. The dashed lines represent an association. X = Explanatory, Y = Response, Z = Lurking

If an experiment is not possible… The association is strong. The association is consistent. Higher doses are associated with stronger responses. The alleged cause precedes the effect in time. The alleged cause is plausible. You need to make sure you can prove the following to establish causation when you cannot perform an experiment:

Now for you and your groups… Create 5 confounding diagrams (of each type) related to different topics. Make sure you use different variables (especially different lurking variables, each time).