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Esamina i metodi selezionati fianco a fianco; le righe che differiscono sono evidenziate.
| Ricerca Gerarchica tramite Sondaggio× | Ricerca su Panel× | |
|---|---|---|
| Campo | Disegno della ricerca | Disegno della ricerca |
| Famiglia | Process / pipeline | Process / pipeline |
| Anno di origine≠ | 1986–1992 (formalization of multilevel methods for nested survey data) | 1970s-1980s (econometric formalization); earlier social survey use from 1940s |
| Ideatore≠ | Developed through contributions of Aitkin, Longford, Goldstein, Bryk, and Raudenbush in the 1980s–1990s | Social science and econometric traditions; systematized by Cheng Hsiao and others from the 1970s-1980s |
| Tipo≠ | Quantitative survey design with multilevel analysis | Quantitative longitudinal observational design |
| Fonte seminale≠ | Snijders, T. A. B., & Bosker, R. J. (2012). Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling (2nd ed.). Sage. ISBN: 978-1849202015 | Hsiao, C. (2003). Analysis of Panel Data (2nd ed.). Cambridge University Press. ISBN: 978-0521522717 |
| Alias | multilevel survey research, nested survey design, multilevel survey design, HLM-based survey research | panel study, panel survey, longitudinal panel, repeated-measures panel |
| Correlati≠ | 6 | 3 |
| Sintesi≠ | Hierarchical survey research is a quantitative design that collects survey data from respondents who are naturally nested within higher-level units — such as students within classrooms, employees within organizations, or patients within hospitals — and uses multilevel (hierarchical linear) modeling to analyze variation at each level simultaneously. It is the standard approach whenever survey data have a clustered structure that would violate the independence assumption of ordinary regression. | Panel research is a quantitative longitudinal design in which the same individuals, organizations, or other units are measured repeatedly across two or more time points. Unlike cross-sectional surveys that capture a single snapshot, a panel tracks change within units, enabling researchers to separate genuine within-unit change from between-unit differences and to model causal dynamics over time. |
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