Consider that we want to estimate health insurance coverage in Baltimore city.
We could take a random sample of 100 households(HH). In that case, we need a
sampling list of Baltimore HHs. If the list is not available, we need to conduct a
census of HHs. The complete coverage of Baltimore city is required so that all
HHs are listed, which could be expensive. Furthermore, since our sample size is
small compared to the numbers of total HHs, we need to sample only few, say
one or two, in each block (subdivisions). Alternatively, we could select 5 blocks
(say the city is divided into 200 blocks), and in each block interview 20 HHs. We
need to construct HH listing frame only for 5 blocks (less time and costs needed).
Furthermore, by limiting the survey to a smaller area, additional costs will be
saved during the execution of interviews.
Such sampling strategy is known as “cluster sam