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| 종단 모형 검증 연구× | 확증적 연구× | |
|---|---|---|
| 분야 | 연구설계 | 연구설계 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1970s–1990s (SEM foundations by Joreskog 1970; longitudinal SEM elaborated through 1990s–2000s) | 1934 (Popper); widely adopted in social sciences from 1960s onward |
| 창시자≠ | Synthesized from longitudinal panel design and SEM tradition (Joreskog, Bollen, Singer & Willett) | Karl Popper (falsificationism); formalized in behavioral sciences by Paul Meehl and others |
| 유형≠ | Quantitative, confirmatory, longitudinal design | Quantitative research design |
| 원전≠ | Singer, J. D., & Willett, J. B. (2003). Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence. Oxford University Press. ISBN: 978-0195152968 | Popper, K. R. (1959). The Logic of Scientific Discovery. Hutchinson. ISBN: 978-0415278447 |
| 별칭 | longitudinal confirmatory modeling, longitudinal SEM, panel model testing, longitudinal structural modeling | hypothesis-testing research, deductive research, theory-testing research, confirmatory study |
| 관련≠ | 6 | 4 |
| 요약≠ | Longitudinal model testing research combines repeated measurement across time with formal, a priori structural modeling to confirm or disconfirm hypothesized relationships among constructs. Rather than simply describing change, it tests whether a pre-specified theoretical model — typically a structural equation model or growth model — fits observed data collected at two or more time points. This design supports causal inference more convincingly than cross-sectional approaches by capturing temporal ordering of variables. | Confirmatory research is a deductive quantitative design in which the researcher specifies hypotheses derived from existing theory before data collection, then tests whether the data support or refute those hypotheses. Unlike exploratory approaches that generate ideas from data, confirmatory research begins with an established theoretical framework, pre-registers predictions, and applies statistical tests to evaluate those predictions against empirical evidence. It is the backbone of hypothesis-driven social, behavioral, and health science inquiry. |
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