Cluster sampling is a method of probability sampling which involves dividing a population into groups or clusters, randomly selecting some of those clusters, and then including all individuals within the selected clusters in the sample. This method is beneficial when it is costly or impractical to obtain a complete list of the population, as it allows researchers to work with pre-existing groups.
Some advantages of cluster sampling are:
- Cost-effective: Cluster sampling can be more cost-effective than other sampling methods, especially when obtaining a comprehensive list of the entire population is difficult or expensive.
- Logistically feasible: Particularly useful when the population is large and geographically dispersed, making it challenging to access all individuals.
- Saves time: Cluster sampling may save time, as researchers can focus on a subset of clusters rather than attempting to reach every individual in the entire population.
Some challenges faced during cluster sampling include:
- Cluster homogeneity: If clusters are highly homogeneous, the method may result in less variability within the sample compared to other sampling methods.
- Intra-cluster similarity: Individuals within a cluster can be more similar to each other than individuals across different clusters, potentially affecting the generalizability of findings.
- Loss of precision: Cluster sampling may result in less precision than other probability sampling methods, especially when clusters are highly varied.
- Sampling error: If clusters are not truly representative of the population, sampling error could occur, impacting the accuracy of generalizations.
- Increased variability: The variability within clusters should ideally be lower than the variability in the entire population to ensure the method’s effectiveness.
Cluster sampling is a valuable method in situations where obtaining a complete list of the population is challenging or impractical. While it may introduce some challenges, it offers practical advantages in terms of cost and logistics, making it a suitable choice for specific research contexts.
List of recommended resources #
For a broad overview #
Cluster Sampling | A Simple Step-by-Step Guide with Examples
This blog on Scribbr by Lauren Thomas gives an overview and step-by-step guide to cluster sampling. It lists the advantages and disadvantages of cluster sampling as well as explains multistage cluster sampling.
Cluster Sampling: Techniques and Best Practices
This blog by Lauren Stewart for ATLAS.ti gives a broad overview of cluster sampling, types of cluster sampling, its advantages and disadvantages as well as examples and applications of cluster sampling. #
For in depth understanding #
Chapter 9 Cluster Sampling Area sampling Examples
This chapter module by IIT Kanpur gives an in-depth understanding of cluster sampling, the conditions under which cluster sampling is used. It also compares cluster sampling with simple random sampling as well as sampling with replacement and unequal probabilities.
Choosing the type of probability sampling
This chapter from the book Sampling Essentials by Sage Publications gives an in-depth understanding of the different types of probability sampling as well as the differences between them. It also details the strengths and weaknesses of each probability sampling method.
Case study #
This article presents a two-stage cluster sampling method for application in population-based mortality surveys. The sampling method is then implemented in a household mortality study in Iraq in 2011. The factors affecting methodological quality and feasibility are also described.
Comparison of two cluster sampling methods for health surveys in developing countries
This article by Paul Milligan, Alpha Njie, and Steve Bennett compares two cluster sampling methods – the Expanded Program for Immunization (EPI) scheme and compact segment sampling for rapid cluster sample surveys where an up-to-date household sampling frame is not available to estimate vaccination coverage in Western Region of The Gambia within 3 months of each other in 2000–2001.
References #
Cluster Sampling in Statistics: Definition, Types
What’s the Difference Between Systematic Sampling and Cluster Sampling?
