विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| पायलट क्लस्टर सैंपलिंग× | आनुपातिक क्लस्टर नमूनाकरण× | |
|---|---|---|
| क्षेत्र | सर्वेक्षण पद्धति | सर्वेक्षण पद्धति |
| परिवार | Process / pipeline | Process / pipeline |
| उद्भव वर्ष≠ | Mid-20th century (cluster sampling foundations); 2000s (pilot study formalization) | 1950s–1960s |
| प्रवर्तक≠ | Rooted in W. G. Cochran's cluster sampling theory (1953) combined with pilot-study methodology formalized by Lancaster, Dodd & Williamson (2004) and Thabane et al. (2010) | Formalized by William G. Cochran and Leslie Kish |
| प्रकार≠ | Probability sampling feasibility design | Probability sampling design |
| मौलिक स्रोत≠ | Thabane, L., Ma, J., Chu, R., Cheng, J., Ismaila, A., Rios, L. P., & Goldsmith, C. H. (2010). A tutorial on pilot studies: the what, why and how. BMC Medical Research Methodology, 10(1), 1. DOI ↗ | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407 |
| उपनाम | pilot area sampling, feasibility cluster sample, preliminary cluster survey, pilot cluster survey | PPS cluster sampling, proportional-to-size cluster sampling, size-proportional cluster sampling, probability proportional to size sampling |
| संबंधित≠ | 4 | 6 |
| सारांश≠ | Pilot cluster sampling is the application of a cluster sampling protocol on a small, preliminary scale to evaluate the feasibility, logistics, and parameter estimates needed before committing to a full-scale cluster survey. A subset of clusters is randomly selected and fully surveyed, yielding estimates of the intraclass correlation (ICC), design effect, recruitment rates, and operational costs. These findings directly inform the sample size and cluster allocation of the definitive survey. | 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. |
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