Written for students and researchers who wish to understand the conceptual and practical aspects of sampling, this book is designed to be accessible without requiring advanced statistical training. It covers a wide range of topics, from the basics of sampling to special topics such as sampling rare populations, sampling organizational populations, and sampling visitors to a place. Using cases and examples to illustrate sampling principles and procedures, the book thoroughly covers the fundamentals of modern survey sampling, and addresses recent changes in the survey environment such as declining response rates, the rise of Internet surveys, the need to accommodate cell phones in telephone surveys, and emerging uses of social media and big data.

Cluster Sampling

Cluster sampling, like stratified sampling, can improve the cost-effectiveness of research under certain conditions. In cluster sampling, the population is found in subgroups called clusters, and a sample of clusters is drawn. Further sampling of population members may be done within clusters, and multistage cluster sampling is possible (i.e., sampling clusters within clusters). For example, in a study of schoolchildren, we might draw a sample of schools, then classrooms within schools. Exhibit 6.1 provides a graphic depiction of cluster sampling.

Cluster sampling differs from stratified sampling in that cluster sampling uses a sample of clusters, while stratified sampling draws a sample within every stratum. Cluster sampling also differs from stratified sampling in that stratified sampling is focused on reducing sampling errors, while cluster ...

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