Sammenlign metoder

	Forskning på longitudinell modelltesting	Bekreftende forskning
Fagfelt	Forskningsdesign	Forskningsdesign
Familie	Process / pipeline	Process / pipeline
Opprinnelsesår	1970s–1990s (SEM foundations by Joreskog 1970; longitudinal SEM elaborated through 1990s–2000s)	1934 (Popper); widely adopted in social sciences from 1960s onward
Opphavsperson	Synthesized from longitudinal panel design and SEM tradition (Joreskog, Bollen, Singer & Willett)	Karl Popper (falsificationism); formalized in behavioral sciences by Paul Meehl and others
Type	Quantitative, confirmatory, longitudinal design	Quantitative research design
Opprinnelig kilde	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
Alias	longitudinal confirmatory modeling, longitudinal SEM, panel model testing, longitudinal structural modeling	hypothesis-testing research, deductive research, theory-testing research, confirmatory study
Relaterte	6	4
Sammendrag	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.