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| 基于面板的关系调查× | 面板研究× | |
|---|---|---|
| 领域 | 研究设计 | 研究设计 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1940s onward (panel survey); relational survey as standard practice by mid-20th century | 1970s-1980s (econometric formalization); earlier social survey use from 1940s |
| 提出者≠ | Rooted in panel survey traditions systematized by Paul Lazarsfeld (1940s) and relational survey methodology codified by Kerlinger, Babbie, and de Leeuw | Social science and econometric traditions; systematized by Cheng Hsiao and others from the 1970s-1980s |
| 类型≠ | Quantitative observational longitudinal survey design | Quantitative longitudinal observational design |
| 开创性文献≠ | de Leeuw, E. D., Hox, J. J., & Dillman, D. A. (Eds.). (2008). International Handbook of Survey Methodology. Lawrence Erlbaum Associates / Taylor & Francis. ISBN: 978-0805857535 | Hsiao, C. (2003). Analysis of Panel Data (2nd ed.). Cambridge University Press. ISBN: 978-0521522717 |
| 别名 | longitudinal relational survey, panel relational study, repeated-measures correlational survey, panel correlational design | panel study, panel survey, longitudinal panel, repeated-measures panel |
| 相关≠ | 4 | 3 |
| 摘要≠ | A panel-based relational survey is a quantitative design that recruits the same group of respondents and surveys them at two or more time points to examine how variables relate to, predict, or co-vary with one another over time. By combining the relational goal of uncovering associations among variables with the panel structure of repeated measurement from a stable sample, the design enables researchers to track how relationships evolve, test directional hypotheses about predictors and outcomes, and distinguish within-person change from between-person differences. | 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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