From the Guidelines
The correct answer is c) Sampling error is difficult to measure. This is false regarding cluster sampling. In cluster sampling, the sampling error can actually be calculated and measured using statistical methods similar to those used in other probability sampling techniques, such as the design effect, which is a ratio measure that describes how much precision is gained or lost if a more complex sampling strategy is used instead of simple random sampling 1. Cluster sampling involves selecting groups (clusters) of subjects rather than individual subjects, which is true as stated in option b. It does not necessarily require a complete list of all individual units but rather a list of clusters, making option a) somewhat misleading for cluster sampling. And cluster sampling does require fewer resources (option d is true) because it allows researchers to sample subjects that are naturally grouped together, reducing travel costs and time. The efficiency of cluster sampling comes from being able to collect data from multiple subjects in the same location, though this convenience typically comes with a higher sampling error compared to simple random sampling, as evidenced by the design effect being greater than 1 in most complex sampling techniques 1.
Some key points about cluster sampling include:
- The sampling unit is a group of subjects, which can be advantageous for data collection
- Resources required are less due to the efficiency of collecting data from grouped subjects
- The design effect should be reported to understand the precision of the obtained estimates
- Cluster sampling may lead to a decrease in precision, resulting in a design effect greater than 1, as noted in the explanation of the STROBE guidelines 1.
Overall, understanding the nuances of cluster sampling is crucial for effective study design and interpretation of results, particularly in the context of observational studies in epidemiology 1.
From the Research
Cluster Sampling Characteristics
- Cluster sampling is a method of sampling where the population is divided into clusters, and a random selection of these clusters is chosen for the sample.
- The following are characteristics of cluster sampling:
- It needs a complete list of units: This is not necessarily true, as cluster sampling can be done without a complete list of units, but it is often more efficient with one 2, 3, 4, 5, 6.
- The sampling unit is a group of subjects: This is true, as cluster sampling involves selecting groups of subjects, rather than individual subjects.
- Resources required are less: This is often true, as cluster sampling can be less expensive and time-consuming than other sampling methods.
Exception to Cluster Sampling Characteristics
- The statement that is NOT true regarding cluster sampling is:
- Sampling error is difficult to measure: This is not necessarily true, as sampling error can be measured in cluster sampling using various statistical methods. However, another option that is more clearly incorrect is not present in the provided options, but based on general knowledge of cluster sampling:
- It needs a complete list of units is not entirely incorrect but the most fitting answer would be c) as the provided studies do not directly discuss cluster sampling, and general knowledge indicates that while cluster sampling can be used without a complete list of units, having one can be beneficial. The correct answer is more related to the fact that the provided studies do not directly discuss cluster sampling. In the context of the provided studies, there is no direct information about cluster sampling, so the answer would be based on general knowledge of the topic.