Compara mètodes

	Investigació de confirmació	Investigació de contrastació de models
Camp	Disseny de recerca	Disseny de recerca
Família	Process / pipeline	Process / pipeline
Any d'origen	1934 (Popper); widely adopted in social sciences from 1960s onward	1970s (Joreskog 1969–1973); widely adopted in social sciences by the 1980s–1990s
Autor original	Karl Popper (falsificationism); formalized in behavioral sciences by Paul Meehl and others	Karl G. Joreskog (SEM/LISREL framework); formalized through structural equation modeling tradition
Tipus	Quantitative research design	Confirmatory quantitative research design
Font seminal	Popper, K. R. (1959). The Logic of Scientific Discovery. Hutchinson. ISBN: 978-0415278447	Kline, R. B. (2015). Principles and Practice of Structural Equation Modeling (4th ed.). Guilford Press. ISBN: 978-1462523344
Àlies	hypothesis-testing research, deductive research, theory-testing research, confirmatory study	model-based research, structural model testing, theory-testing research, MTR
Relacionats	4	5
Resum	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.	Model testing research is a confirmatory quantitative design in which the researcher specifies a theoretical model — depicting hypothesized relationships among constructs — and then tests how well that model fits empirical data. Drawing primarily on structural equation modeling (SEM) and confirmatory factor analysis (CFA), it evaluates whether the data-implied covariance structure is consistent with the theoretically derived one, yielding fit indices that indicate model-data correspondence.