Methoden vergleichen

	Longitudinale konfirmatorische Forschung – Hypothesen über die Zeit testen	Bestätigende Forschung – Theorieprüfendes quantitatives Design
Fachgebiet	Forschungsdesign	Forschungsdesign
Familie	Process / pipeline	Process / pipeline
Entstehungsjahr	1970s onward; consolidated in SEM literature from 1990s	1934 (Popper); widely adopted in social sciences from 1960s onward
Urheber	Synthesized from longitudinal design traditions (e.g., Baltes & Nesselroade, 1979) and confirmatory analytic frameworks (Joreskog, 1969)	Karl Popper (falsificationism); formalized in behavioral sciences by Paul Meehl and others
Typ	Quantitative research design	Quantitative research design
Wegweisende Quelle	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
Aliasnamen	longitudinal confirmatory study, confirmatory longitudinal design, longitudinal hypothesis-testing design, longitudinal CFA design	hypothesis-testing research, deductive research, theory-testing research, confirmatory study
Verwandt	5	4
Zusammenfassung	Longitudinal confirmatory research combines the temporal depth of longitudinal design with the hypothesis-driven logic of confirmatory analysis. The researcher specifies a priori hypotheses or structural models about how variables change or remain stable over time, then tests those predictions against data collected at two or more time points. It is the design of choice when theory is mature enough to make specific predictions about developmental, causal, or stability processes.	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.