Comparer des méthodes

	Analyse de variance à un facteur	ANOVA à mesures répétées	Modélisation par équations structurelles (MES)
Domaine	Statistique	Statistique	Statistique
Famille	Hypothesis test	Hypothesis test	Latent structure
Année d'origine	1925	1992	1970
Auteur d'origine	Ronald A. Fisher	Girden (textbook treatment); Field (2013)	Karl Jöreskog (LISREL framework, 1970s)
Type	Parametric mean comparison	Parametric within-subjects mean comparison	Latent variable / causal modeling
Source fondatrice	Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd.	Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed., Ch. 14). SAGE. ISBN: 978-1446249185	Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage Learning. ISBN: 978-1473756540
Alias	one-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA	within-subjects ANOVA, repeated measures analysis of variance, rm-ANOVA, Tekrarlı Ölçüm ANOVA	Yapısal Eşitlik Modellemesi (SEM), structural equation modelling, covariance structure analysis, latent variable modeling
Apparentées	4	4	5
Résumé	One-way ANOVA is a parametric hypothesis test that compares the means of three or more independent groups on a single continuous outcome to decide whether at least one group mean differs. It rests on the variance-partitioning framework introduced by Ronald A. Fisher in 1925.	Repeated-measures ANOVA is a parametric hypothesis test that compares three or more measurements taken from the same individuals — typically across time points or conditions — to decide whether their means differ. It extends one-way ANOVA to within-subjects designs, as treated in standard references such as Girden (1992) and Field (2013).	Structural equation modeling is a multivariate statistical framework that simultaneously estimates a measurement model — relating observed indicators to latent constructs — and a structural model specifying directional or reciprocal relationships among those constructs. Rooted in the LISREL tradition developed by Karl Jöreskog in the 1970s, SEM is the standard tool for testing complex theoretical models in the social, behavioural, and management sciences.