Comparer des méthodes

	Recherche de test de modèle	Recherche causale-comparative
Domaine	Conception de la recherche	Conception de la recherche
Famille	Process / pipeline	Process / pipeline
Année d'origine	1970s (Joreskog 1969–1973); widely adopted in social sciences by the 1980s–1990s	1964
Auteur d'origine	Karl G. Joreskog (SEM/LISREL framework); formalized through structural equation modeling tradition	Fred N. Kerlinger
Type	Confirmatory quantitative research design	Non-experimental quantitative research design
Source fondatrice	Kline, R. B. (2015). Principles and Practice of Structural Equation Modeling (4th ed.). Guilford Press. ISBN: 978-1462523344	Kerlinger, F. N. (1964). Foundations of Behavioral Research. Holt, Rinehart and Winston.
Alias	model-based research, structural model testing, theory-testing research, MTR	ex post facto research, causal-comparative design, retrospective causal study, CCR
Apparentées	5	3
Résumé	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.	Causal-comparative research is a non-experimental quantitative design in which the researcher compares two or more groups that already differ on an independent variable — one that was not manipulated — to investigate possible causes or consequences of that difference. Because group membership is pre-existing rather than randomly assigned, the design can suggest causal relationships but cannot establish them with the certainty of a true experiment. It is widely used in education, psychology, and social sciences when experimental manipulation is impractical or unethical.