Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Daudzlīmeņu mērķtiecīga atlase× | Klasteru izlase× | |
|---|---|---|
| Nozare | Aptauju metodoloģija | Aptauju metodoloģija |
| Saime | Process / pipeline | Process / pipeline |
| Izcelsmes gads≠ | 1980s–1990s | Early-to-mid 20th century; canonical treatment 1953/1977 |
| Autors≠ | Derived from Patton's purposive sampling framework; formalized in multi-site qualitative and mixed-methods research | Formalized by William G. Cochran; roots in early 20th-century U.S. Census Bureau survey practice |
| Tips≠ | Non-probability sampling strategy | Probability sampling design |
| Pirmavots≠ | Patton, M. Q. (2002). Qualitative Research and Evaluation Methods (3rd ed.). Sage. ISBN: 978-0761919711 | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0471162407 |
| Citi nosaukumi≠ | hierarchical purposive sampling, nested purposive sampling, multi-tier purposive sampling, multi-site purposive sampling | cluster random sampling, area sampling, one-stage cluster sampling |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | Multi-level purposive sampling applies purposive selection criteria at two or more nested levels of a research hierarchy — for instance, first selecting sites or organizations, then selecting participants within each site. This layered approach allows researchers to align the theoretical logic of purposive sampling with the real-world structure of complex, hierarchical populations, making it especially valuable in multi-site qualitative studies and mixed-methods research. | 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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