Unintentional Interlocking Quotas

This post has been written in response to a query I receive fairly often about sampling. The phenomenon it looks at relates to the very weird effects that can occur when a researcher uses non-interlocking quotas, effects that I am calling unintentional quotas, for example when using an online access panel. In many studies, quota controls are used to try to achieve a sample to match a) the population and/or b) the target groups needed for analysis. Quota controls fall into two categories, interlocking and non-interlocking. The difference between the two types can be shown with a simple example, using gender (Male and Female) and colour preference (Red or Blue). If we know that 80% of Females prefer Red, if we know that 80% of Men prefer Blue, and if there are an equal number of Males and Females in our target population, then we can create interlocking quotas. In our example we will assume that the total sample size wanted is 200. Males who prefer Red = 50% * 20% * 200 = 20 Males who prefer Blue = 50% * 80% * 200 = 80 Females who prefer Red = 50% * 80% * 200 = 80 Females […]