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| Panelowa badania przyczynowo-porównawcze× | Badania podłużne× | |
|---|---|---|
| Dziedzina | Projektowanie badań | Projektowanie badań |
| Rodzina | Process / pipeline | Process / pipeline |
| Rok powstania≠ | 1950s–1980s (formalized across educational and social science methodology literature) | Late 19th–early 20th century; methodologically codified through the 20th century |
| Twórca≠ | Building on causal-comparative tradition (John W. Best, 1959) extended to panel data structures in social and educational research | No single originator; foundational methodological treatments by Stuart Menard and Judith Singer & John Willett |
| Typ≠ | Quantitative observational research design | Quantitative (or mixed) observational research design |
| Źródło pierwotne≠ | Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2019). How to Design and Evaluate Research in Education (10th ed.). McGraw-Hill. ISBN: 978-1260087840 | Menard, S. (2002). Longitudinal Research (2nd ed.). Sage Publications. ISBN: 978-0761922841 |
| Inne nazwy | panel causal-comparative design, longitudinal ex post facto research, panel ex post facto study, repeated-measures causal-comparative study | longitudinal study, longitudinal design, prospective longitudinal study, repeated-measures observational study |
| Pokrewne≠ | 5 | 4 |
| Podsumowanie≠ | Panel-based causal-comparative research is a quantitative observational design that tracks the same sample of participants or units across multiple time points and then compares pre-existing groups to identify differences in outcomes. By combining the temporal depth of a panel structure with the group-contrast logic of causal-comparative (ex post facto) methodology, it allows researchers to examine how naturally occurring conditions — such as treatment exposure, policy changes, or demographic characteristics — relate to outcomes over time, without experimental random assignment. | 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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