notes 11 - Basic Principles of Statistical Design of...

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Basic Principles of Statistical Design of Experiments Submitted by gfj100 on Tue, 11/10/2009 - 16:29 Example A group of college students believe that regular consumption of a special Asian tea could benefit the health of patients in a nearby nursing home. Each week they go the rooms of 5 or 6 patients who agree to drink the hot tea. After a few months the students see considerable improvement in the conditions of those patients who received the tea. Is this an experiment? Yes – there is a treatment imposed: the Asian tea. Is it a good experiment? No – there is no control, no randomization, and not enough replication. 1. In a good design, we control for the effects of outside variables. To avoid confounding the effect of the treatment with other variables, (e.g. welcomed attention, overall health), a comparison should be made. For example, while some patients receive Asian tea, other should receive another hot liquid, for example coffee of cocoa. The study in the example was biased because it systematically favored the outcome of improved well-being. Such bias is typical in situations where the placebo effect can come into play: even a dummy treatment, such as a sugar pill, can lead to perceived improvement. 2. Randomization – relying on chance to decide which subjects are studied and which get what treatment – is usually the best way to ensure that bias does not creep into the initial selection. Then all treatments are applied to similar groups of experimental units. If
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notes 11 - Basic Principles of Statistical Design of...

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