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Daudzlīmeņu mērķtiecīga atlase×Klasteru izlase×
NozareAptauju metodoloģijaAptauju metodoloģija
SaimeProcess / pipelineProcess / pipeline
Izcelsmes gads1980s–1990sEarly-to-mid 20th century; canonical treatment 1953/1977
AutorsDerived from Patton's purposive sampling framework; formalized in multi-site qualitative and mixed-methods researchFormalized by William G. Cochran; roots in early 20th-century U.S. Census Bureau survey practice
TipsNon-probability sampling strategyProbability sampling design
PirmavotsPatton, M. Q. (2002). Qualitative Research and Evaluation Methods (3rd ed.). Sage. ISBN: 978-0761919711Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0471162407
Citi nosaukumihierarchical purposive sampling, nested purposive sampling, multi-tier purposive sampling, multi-site purposive samplingcluster random sampling, area sampling, one-stage cluster sampling
Saistītās55
KopsavilkumsMulti-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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ScholarGateSalīdzināt metodes: Multi-level Purposive Sampling · Cluster Sampling. Izgūts 2026-06-15 no https://scholargate.app/lv/compare