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| 종단적 설명 연구× | 설명 연구× | |
|---|---|---|
| 분야 | 연구설계 | 연구설계 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1970s–1990s (formal methodological codification) | 1960s–1980s (codified in behavioral and social science methodology) |
| 창시자≠ | Rooted in panel and longitudinal survey traditions; systematised by Scott Menard and others in the late 20th century | Formalized by Earl Babbie and Fred Kerlinger among others |
| 유형≠ | Quantitative observational research design | Non-experimental quantitative research design |
| 원전≠ | Menard, S. (2002). Longitudinal Research (2nd ed.). Sage Publications. ISBN: 978-0761922452 | Kerlinger, F. N. (1986). Foundations of Behavioral Research (3rd ed.). Holt, Rinehart and Winston. ISBN: 978-0030417559 |
| 별칭 | explanatory longitudinal design, longitudinal causal research, explanatory panel study, longitudinal explanatory study | analytical research, causal research, explanatory study, explanatory quantitative research |
| 관련≠ | 4 | 5 |
| 요약≠ | Longitudinal explanatory research combines repeated measurement over time with an explicit aim of explaining why and how variables change or influence one another. Unlike purely descriptive longitudinal designs, the explanatory orientation tests causal or predictive hypotheses by examining temporal precedence — a key criterion for causal inference in non-experimental settings. It is widely used in social, behavioral, educational, and health sciences to disentangle cause from correlation. | Explanatory research is a non-experimental quantitative research design that goes beyond describing a phenomenon to identifying why it occurs — examining the relationships or mechanisms that account for observed patterns. Rooted in positivist social science methodology, it uses theory-driven hypotheses and statistical analysis to test whether specific variables explain variation in an outcome, without necessarily manipulating those variables. |
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