विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| पदानुक्रमित अनुप्रस्थ-अनुभागीय अनुसंधान× | क्लस्टर सैंपलिंग (Cluster Sampling)× | |
|---|---|---|
| क्षेत्र≠ | अनुसंधान अभिकल्प | सर्वेक्षण पद्धति |
| परिवार | Process / pipeline | Process / pipeline |
| उद्भव वर्ष≠ | 1980s–1990s (formalized with HLM software and methodology) | Early-to-mid 20th century; canonical treatment 1953/1977 |
| प्रवर्तक≠ | Raudenbush & Bryk; Goldstein; Snijders & Bosker (multilevel modeling tradition) | Formalized by William G. Cochran; roots in early 20th-century U.S. Census Bureau survey practice |
| प्रकार≠ | Quantitative observational design | Probability sampling design |
| मौलिक स्रोत≠ | Snijders, T. A. B., & Bosker, R. J. (2012). Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling (2nd ed.). Sage. ISBN: 978-1849202015 | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0471162407 |
| उपनाम≠ | multilevel cross-sectional design, nested cross-sectional study, clustered cross-sectional research, HCS design | cluster random sampling, area sampling, one-stage cluster sampling |
| संबंधित≠ | 2 | 5 |
| सारांश≠ | Hierarchical cross-sectional research is a quantitative observational design that collects data from individuals nested within higher-level units — such as students within schools, patients within hospitals, or employees within organizations — at a single point in time. By accounting for the non-independence of clustered observations through multilevel modeling, it enables researchers to simultaneously examine individual-level and group-level predictors of an outcome without violating the independence assumption of ordinary regression. | 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. |
| ScholarGateडेटासेट ↗ |
|
|