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| Panel alapú keresztmetszeti kutatás – Tervezés és alkalmazás× | Hossz-menti kutatás× | |
|---|---|---|
| Tudományterület | Kutatástervezés | Kutatástervezés |
| Módszercsalád | Process / pipeline | Process / pipeline |
| Keletkezés éve≠ | 1940s–1960s (formalized in social survey methodology) | Late 19th–early 20th century; methodologically codified through the 20th century |
| Megalkotó≠ | Panel survey methodology developed from large-scale government and social survey programs (e.g., University of Michigan Survey Research Center, 1940s–1950s) | No single originator; foundational methodological treatments by Stuart Menard and Judith Singer & John Willett |
| Típus≠ | Quantitative observational design | Quantitative (or mixed) observational research design |
| Alapmű≠ | Kasprzyk, D., Duncan, G., Kalton, G., & Singh, M. P. (Eds.). (1989). Panel Surveys. John Wiley & Sons. ISBN: 978-0471622635 | Menard, S. (2002). Longitudinal Research (2nd ed.). Sage Publications. ISBN: 978-0761922841 |
| Alternatív nevek | panel cross-sectional survey, rotating panel cross-section, repeated cross-section panel, cross-sectional panel design | longitudinal study, longitudinal design, prospective longitudinal study, repeated-measures observational study |
| Kapcsolódó≠ | 3 | 4 |
| Összefoglaló≠ | Panel-based cross-sectional research draws repeated cross-sectional measurements from a pre-recruited standing panel rather than sampling fresh respondents each time. This hybrid design preserves the snapshot character of classic cross-sectional surveys while gaining speed, cost efficiency, and comparability across waves. It is widely used in social, health, and market research whenever population-level estimates are needed quickly and repeatedly without full longitudinal tracking of the same individuals. | Longitudinal research is an observational design in which the same participants, groups, or units are measured repeatedly over an extended period. Rather than capturing a single snapshot, it tracks change, stability, and temporal sequencing of variables — making it the primary non-experimental strategy for studying development, growth, decline, and the unfolding of causal processes across time. |
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