2. What is Randomisation?

2.2. Randomisation Using Cluster Sampling

Cluster sampling is a sampling technique that has been used when ‘natural’ but relatively homogeneous groups are evident in a population. In this technique, the total population is divided into these groups (or clusters) and a simple random sample of the groups is selected. Then the required information is collected within each selected group. This may be done for every element in these groups.

The population within a cluster should ideally be as heterogeneous as possible. Each cluster should be a small-scale representation of the total population.
For example :

  • Determine suitable geographical areas (e.g. catchment area, city, country, etc.).
  • Randomly choose a number of these geographical areas.
  • For each of these chosen geographical areas, choose a proportional sub-sample from the members of the study population in that area.
  • Combine these sub-samples to get a sample group.
This form of sampling is generally useful for interviews however it could be useful for clinical trials if there are multiple clinics or hospitals that can take part in the study.