Comparer des méthodes

	Tests d'hypothèses longitudinales	ANOVA à mesures répétées
Domaine	Conception de la recherche	Statistique
Famille	Process / pipeline	Hypothesis test
Année d'origine	Consolidated as a formal design framework in the 1960s–1980s	1992
Auteur d'origine	Synthesized from longitudinal design traditions (Lazarsfeld, 1940s) and classical hypothesis testing (Fisher, Neyman-Pearson, 1920s–1930s)	Girden (textbook treatment); Field (2013)
Type	Quantitative longitudinal research design	Parametric within-subjects mean comparison
Source fondatrice	Singer, J. D., & Willett, J. B. (2003). Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence. Oxford University Press. ISBN: 978-0195152968	Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed., Ch. 14). SAGE. ISBN: 978-1446249185
Alias	longitudinal confirmatory study, repeated-measures hypothesis testing, prospective hypothesis testing, longitudinal inferential research	within-subjects ANOVA, repeated measures analysis of variance, rm-ANOVA, Tekrarlı Ölçüm ANOVA
Apparentées	5	4
Résumé	Longitudinal hypothesis testing research combines a longitudinal design — measuring the same units repeatedly over time — with formal null-hypothesis significance testing to determine whether observed changes exceed what chance alone can explain. It is widely used in education, medicine, psychology, and social science to test directional predictions about change, stability, or group differences that emerge over a defined time span.	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).