Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Eșantionarea multinivelară pe grupe× | Eșantionarea pe grupe (Cluster Sampling)× | |
|---|---|---|
| Domeniu | Metodologia anchetelor | Metodologia anchetelor |
| Familie | Process / pipeline | Process / pipeline |
| Anul apariției≠ | 1950s-1970s (cluster sampling); multilevel extension formalized 1980s-1990s | Early-to-mid 20th century; canonical treatment 1953/1977 |
| Autorul original≠ | W. G. Cochran (cluster sampling foundations); extended into multilevel contexts by survey methodologists | Formalized by William G. Cochran; roots in early 20th-century U.S. Census Bureau survey practice |
| Tip | Probability sampling design | Probability sampling design |
| Sursa seminală | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0471162407 | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0471162407 |
| Denumiri alternative≠ | hierarchical cluster sampling, nested cluster sampling, multi-stage cluster sampling, clustered multilevel sampling | cluster random sampling, area sampling, one-stage cluster sampling |
| Înrudite≠ | 6 | 5 |
| Rezumat≠ | Multi-level cluster sampling is a probability sampling design for hierarchically structured populations — such as students nested within classrooms within schools within districts. Clusters are randomly selected at each level of the hierarchy before individual units are sampled within the final-level clusters. The design mirrors the natural nesting of real-world populations and enables efficient large-scale data collection while supporting multilevel statistical analysis. | 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. |
| ScholarGateSet de date ↗ |
|
|