Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Sampuli za Hatua Nyingi Zinazobadilika× | Usampulishaji wa Hatua Nyingi× | |
|---|---|---|
| Nyanja | Metodolojia ya Dodoso | Metodolojia ya Dodoso |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 1977 (multistage base); 1990-1992 (adaptive extensions by Thompson) | 1950s–1960s (formalized in Kish 1965 and Cochran 1977) |
| Mwanzilishi≠ | Steven K. Thompson (adaptive principles); William G. Cochran (multistage framework) | Leslie Kish; William G. Cochran |
| Aina≠ | Probability-based adaptive sampling design | Probability sampling design |
| Chanzo asilia≠ | Thompson, S. K. (1992). Sampling. Wiley. ISBN: 978-0471548850 | Kish, L. (1965). Survey Sampling. John Wiley & Sons. ISBN: 978-0471109495 |
| Majina mbadala | AMS, adaptive multi-phase sampling, sequential multistage sampling, adaptive hierarchical sampling | multistage cluster sampling, multi-stage sampling, nested sampling, hierarchical sampling |
| Zinazohusiana | 5 | 5 |
| Muhtasari≠ | Adaptive multistage sampling combines the hierarchical efficiency of multistage designs with adaptive decision rules that adjust which units are sampled at later stages based on what is observed at earlier stages. It is used when a target characteristic is rare, clustered, or spatially heterogeneous and a fixed design would waste resources on uninformative areas of the population. | 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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