h1 - Causation

h1 - Causation - Page 1 of 3 Stat 201 Handout Concluding...

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Stat 201 Handout (May 21, 2003) Concluding Causation Q: When can we conclude " treatment causes a change in response "? e.g. " Drug A provides headache relief ." Here, Drug A is the treatment , and relief of headache (as opposed to no change in headache) is the change in response . A: The following are required to make a valid claim of causation: 1. presence of control group -- needed as a baseline for assessing the effects of the treatment 2. no confounding 3. no bias (from subject or investigator) Q: How to control for confounding? A: The only foolproof way is to ensure the treatment and control groups are absolutely equal in every way EXCEPT the treatment itself. e.g. Does Pentium 4 improve CPU speed for a PC? You get 20 identical PC's (with identical parts and chips and everything else), but the first 10 get Pentium 3 while the last 10 get Pentium 4. Now the only difference between the first 10 (control) and the last 10 (treatment) is the Pentium release. (Note : In real life, it is usually impossible to ensure the 20 PC's are absolutely identical due to uncontrollable random elements in the manufacturing process!) The almost -foolproof way to control for confounding is to use random treatment allocation . Randomness tends to balance out differences outside of the treatment
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This note was uploaded on 01/23/2012 for the course STAT 201 taught by Professor Staff during the Fall '03 term at Simon Fraser.

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h1 - Causation - Page 1 of 3 Stat 201 Handout Concluding...

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