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| Online Cluster Sampling× | Cluster-Sampling× | |
|---|---|---|
| Fachgebiet | Umfragemethodik | Umfragemethodik |
| Familie | Process / pipeline | Process / pipeline |
| Entstehungsjahr≠ | Late 1990s–2000s (as internet surveys became prevalent) | Early-to-mid 20th century; canonical treatment 1953/1977 |
| Urheber≠ | Adapted from cluster sampling (Mahalanobis, Hansen & Hurwitz, 1940s) to online survey contexts | Formalized by William G. Cochran; roots in early 20th-century U.S. Census Bureau survey practice |
| Typ≠ | Probability sampling technique | Probability sampling design |
| Wegweisende Quelle≠ | Couper, M. P. (2000). Web surveys: A review of issues and approaches. Public Opinion Quarterly, 64(4), 464–494. DOI ↗ | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0471162407 |
| Aliasnamen | internet cluster sampling, web cluster sampling, digital cluster sampling | cluster random sampling, area sampling, one-stage cluster sampling |
| Verwandt≠ | 4 | 5 |
| Zusammenfassung≠ | Online cluster sampling applies the classic cluster sampling logic to internet-based research: naturally occurring digital groups — such as online communities, email lists, forum memberships, or institutional user registries — serve as clusters, and selected clusters are surveyed in full or partially via web-based instruments. It offers a practical route to probability-based online samples when no complete list of individuals exists but lists of digital groups are accessible. | Cluster sampling is a probability sampling technique in which the population is divided into naturally occurring groups (clusters), a random sample of clusters is selected, and all — or a random subset of — members within each selected cluster are studied. It is especially practical when a complete population list is unavailable or when units are geographically dispersed, making individual random selection prohibitively expensive. One-stage cluster sampling surveys every member of selected clusters; two-stage designs add a second random draw within clusters. |
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