Longitudinal Model Testing Research
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.
Allikakirje
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- Singer, J. D., & Willett, J. B. (2003). Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence. Oxford University Press. · ISBN 978-0195152968
- Kline, R. B. (2016). Principles and Practice of Structural Equation Modeling (4th ed.). Guilford Press. · ISBN 978-1462523344
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