Compara mètodes
Revisa els mètodes seleccionats l'un al costat de l'altre; les files que difereixen es ressalten.
| Investigació Comparativa de Panells× | Investigació Longitudinal× | |
|---|---|---|
| Camp | Disseny de recerca | Disseny de recerca |
| Família | Process / pipeline | Process / pipeline |
| Any d'origen≠ | 1970s–1980s (formal integration of comparative and panel designs) | Late 19th–early 20th century; methodologically codified through the 20th century |
| Autor original≠ | Developed across social science disciplines; seminal formalizations by Cheng Hsiao (panel econometrics) and Melvin Kohn (comparative sociology) | No single originator; foundational methodological treatments by Stuart Menard and Judith Singer & John Willett |
| Tipus≠ | Quantitative longitudinal comparative design | Quantitative (or mixed) observational research design |
| Font seminal≠ | Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. ISBN: 978-1107038691 | Menard, S. (2002). Longitudinal Research (2nd ed.). Sage Publications. ISBN: 978-0761922841 |
| Àlies | cross-national panel study, comparative longitudinal panel, pooled cross-sectional time-series design, multi-group panel design | longitudinal study, longitudinal design, prospective longitudinal study, repeated-measures observational study |
| Relacionats≠ | 3 | 4 |
| Resum≠ | Comparative panel research tracks the same individuals, organizations, or macro-level units (e.g., countries, regions) across multiple time points while simultaneously comparing findings across two or more distinct groups or contexts. By combining the temporal depth of panel measurement with the analytical leverage of systematic comparison, this design can distinguish change processes that are universal from those that are context-specific — a capability neither pure panel nor single-sample longitudinal designs offer on their own. | 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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