Сравнение на методи
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| Изследване с лонгитюдни хипотези× | Панелни изследвания× | |
|---|---|---|
| Област | Дизайн на изследването | Дизайн на изследването |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | Consolidated as a formal design framework in the 1960s–1980s | 1970s-1980s (econometric formalization); earlier social survey use from 1940s |
| Създател≠ | Synthesized from longitudinal design traditions (Lazarsfeld, 1940s) and classical hypothesis testing (Fisher, Neyman-Pearson, 1920s–1930s) | Social science and econometric traditions; systematized by Cheng Hsiao and others from the 1970s-1980s |
| Тип≠ | Quantitative longitudinal research design | Quantitative longitudinal observational design |
| Основополагащ източник≠ | Singer, J. D., & Willett, J. B. (2003). Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence. Oxford University Press. ISBN: 978-0195152968 | Hsiao, C. (2003). Analysis of Panel Data (2nd ed.). Cambridge University Press. ISBN: 978-0521522717 |
| Други названия | longitudinal confirmatory study, repeated-measures hypothesis testing, prospective hypothesis testing, longitudinal inferential research | panel study, panel survey, longitudinal panel, repeated-measures panel |
| Свързани≠ | 5 | 3 |
| Резюме≠ | Longitudinal hypothesis testing research combines a longitudinal design — measuring the same units repeatedly over time — with formal null-hypothesis significance testing to determine whether observed changes exceed what chance alone can explain. It is widely used in education, medicine, psychology, and social science to test directional predictions about change, stability, or group differences that emerge over a defined time span. | 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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