Comparer des méthodes

	Analyse des processus conditionnels (médiation modérée)	Variables instrumentales par moindres carrés en deux étapes (VI/2SLS)
Domaine	Inférence causale	Inférence causale
Famille	Regression model	Regression model
Année d'origine	2018	2009
Auteur d'origine	Andrew F. Hayes (PROCESS framework); Preacher, Rucker & Hayes (moderated mediation)	Angrist & Pischke (textbook treatment); Stock & Yogo (weak-instrument theory)
Type	Regression-based conditional process model	Instrumental-variables regression
Source fondatrice	Hayes, A. F. (2018). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach (2nd ed.). The Guilford Press. ISBN: 978-1462534654	Angrist, J. D. & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Alias	moderated mediation, moderated mediation analysis, PROCESS model, Hayes PROCESS conditional process model	instrumental variables, IV estimation, 2SLS, instrumental variable regression
Apparentées	5	5
Résumé	Conditional process analysis is Andrew F. Hayes's regression-based PROCESS framework (2018) that combines mediation and moderation in a single model, testing how an indirect effect changes across levels of a moderator. It quantifies conditional indirect and conditional direct effects and tests them with bootstrap confidence intervals.	IV/2SLS is a two-stage estimation method that recovers the causal effect of an endogenous regressor by isolating the part of its variation driven by an external instrument. It is the workhorse identification strategy in modern applied econometrics, developed at length in Angrist and Pischke's Mostly Harmless Econometrics (2009).