Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Eșantionarea Clusterizată Proporțională× | Eșantionare multistadială× | |
|---|---|---|
| Domeniu | Metodologia anchetelor | Metodologia anchetelor |
| Familie | Process / pipeline | Process / pipeline |
| Anul apariției≠ | 1950s–1960s | 1950s–1960s (formalized in Kish 1965 and Cochran 1977) |
| Autorul original≠ | Formalized by William G. Cochran and Leslie Kish | Leslie Kish; William G. Cochran |
| Tip | Probability sampling design | Probability sampling design |
| Sursa seminală≠ | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407 | Kish, L. (1965). Survey Sampling. John Wiley & Sons. ISBN: 978-0471109495 |
| Denumiri alternative | PPS cluster sampling, proportional-to-size cluster sampling, size-proportional cluster sampling, probability proportional to size sampling | multistage cluster sampling, multi-stage sampling, nested sampling, hierarchical sampling |
| Înrudite≠ | 6 | 5 |
| Rezumat≠ | Proportional cluster sampling selects naturally occurring groups (clusters) from a population with probability proportional to each cluster's size, so that larger clusters have a higher chance of selection while every individual element retains an equal overall inclusion probability. This design efficiently handles large, geographically dispersed populations and is the backbone of national health, education, and social surveys worldwide. | Multistage sampling is a probability-based design that selects a sample by working through two or more successive levels of a population hierarchy — for example, first selecting regions, then districts within those regions, then households within those districts. It makes large-scale surveys practical when a complete population list is unavailable or when the population is geographically dispersed, by concentrating fieldwork within a manageable number of sampled units at each stage. |
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