Comparer des méthodes

	Recherche causale-comparative assistée par simulation	Recherche causale-comparative
Domaine	Conception de la recherche	Conception de la recherche
Famille	Process / pipeline	Process / pipeline
Année d'origine	Late 20th–early 21st century (hybrid approach formalized ~1990s–2000s)	1964
Auteur d'origine	Synthesized from causal-comparative tradition (Donald T. Campbell; Julian Stanley) and simulation methodology	Fred N. Kerlinger
Type	Hybrid observational-simulation design	Non-experimental quantitative research design
Source fondatrice	Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2019). How to Design and Evaluate Research in Education (10th ed.). McGraw-Hill. ISBN: 978-1260087352	Kerlinger, F. N. (1964). Foundations of Behavioral Research. Holt, Rinehart and Winston.
Alias	simulation-augmented causal-comparative design, ex post facto simulation design, SA-CCR, causal-comparative with simulation validation	ex post facto research, causal-comparative design, retrospective causal study, CCR
Apparentées	4	3
Résumé	Simulation-assisted causal-comparative research is a hybrid observational design that combines the ex post facto logic of causal-comparative studies — comparing groups that differ on a naturally occurring variable — with computational simulation to strengthen causal inference, test counterfactuals, and assess the robustness of observed group differences. By augmenting real-world comparisons with simulated scenarios, researchers can explore causal mechanisms that cannot be manipulated experimentally.	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.