Introduction to the sample size example

It is easiest to understand sample size calculations in the context of an example. The example we'll use is a project I worked on twenty years ago. We didn't really do a formal analysis of sample size back then, but should have. Then in the next example, we'll use a power analysis to help understand the results we actually obtained.

Note: Using StatMate is entirely self-explanatory, and this example emphasizes the logic behind sample size calculations rather than the mechanics of using StatMate.  

First a bit of background. Platelets (the small cells in blood that help with clotting) have alpha₂-adrenergic receptors. Epinephrine (adrenaline) in the blood binds to these receptors, which make the platelets more sticky, so they aggregate, helping blood clot. Hypertension (high blood pressure) is a complicated disease (or group of diseases) but there is lots of evidence that the adrenergic signalling system might be abnormal in hypertension.

We were most interested in the heart, blood vessels, kidney and brain but obviously couldn't access those tissues in people. Instead, we decided to count the number of alpha2-adrenergic receptors on platelets, and compare people with and without hypertension.

How many subjects should we use? When we did this study 20 years ago, we picked sample size more-or-less at whim. But we should have done a proper sample size analysis. In the next few screens, I'll show you how to do so with StatMate.

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