Сравнение на методи
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| Лонгитюдюден експостфакто дизайн× | Панелни изследвания× | |
|---|---|---|
| Област | Дизайн на изследването | Дизайн на изследването |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 1964–1986 (Kerlinger 1964 first edition; Campbell & Stanley 1966) | 1970s-1980s (econometric formalization); earlier social survey use from 1940s |
| Създател≠ | Fred N. Kerlinger (systematized); Donald T. Campbell & Julian C. Stanley (quasi-experimental framework) | Social science and econometric traditions; systematized by Cheng Hsiao and others from the 1970s-1980s |
| Тип≠ | Non-experimental quantitative research design | Quantitative longitudinal observational design |
| Основополагащ източник≠ | Kerlinger, F. N. (1986). Foundations of Behavioral Research (3rd ed.). Holt, Rinehart and Winston. ISBN: 978-0030417498 | Hsiao, C. (2003). Analysis of Panel Data (2nd ed.). Cambridge University Press. ISBN: 978-0521522717 |
| Други названия | longitudinal causal-comparative design, longitudinal after-the-fact design, longitudinal retrospective design, LEPF design | panel study, panel survey, longitudinal panel, repeated-measures panel |
| Свързани≠ | 5 | 3 |
| Резюме≠ | A longitudinal ex post facto design combines the time-depth of longitudinal research with the retrospective logic of ex post facto inquiry. Participants are grouped by a naturally occurring characteristic or past event — not randomly assigned — and then observed or measured at multiple points over time. The goal is to trace how pre-existing differences between groups unfold or predict outcomes across an extended period, without the researcher ever manipulating the independent variable. | 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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