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| Pengujian Model Longitudinal× | Penelitian Panel× | |
|---|---|---|
| Bidang | Desain Penelitian | Desain Penelitian |
| Keluarga | Process / pipeline | Process / pipeline |
| Tahun asal≠ | 1970s–1990s (SEM foundations by Joreskog 1970; longitudinal SEM elaborated through 1990s–2000s) | 1970s-1980s (econometric formalization); earlier social survey use from 1940s |
| Pencetus≠ | Synthesized from longitudinal panel design and SEM tradition (Joreskog, Bollen, Singer & Willett) | Social science and econometric traditions; systematized by Cheng Hsiao and others from the 1970s-1980s |
| Tipe≠ | Quantitative, confirmatory, longitudinal design | Quantitative longitudinal observational design |
| Sumber perintis≠ | 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 |
| Alias | longitudinal confirmatory modeling, longitudinal SEM, panel model testing, longitudinal structural modeling | panel study, panel survey, longitudinal panel, repeated-measures panel |
| Terkait≠ | 6 | 3 |
| Ringkasan≠ | 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. | 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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