Salīdzināt metodes

	Longitudināla hipotēžu testēšanas izpēte	ANOVA ar atkārtotiem mērījumiem
Nozare	Pētījuma dizains	Statistika
Saime	Process / pipeline	Hypothesis test
Izcelsmes gads	Consolidated as a formal design framework in the 1960s–1980s	1992
Autors	Synthesized from longitudinal design traditions (Lazarsfeld, 1940s) and classical hypothesis testing (Fisher, Neyman-Pearson, 1920s–1930s)	Girden (textbook treatment); Field (2013)
Tips	Quantitative longitudinal research design	Parametric within-subjects mean comparison
Pirmavots	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
Citi nosaukumi	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
Saistītās	5	4
Kopsavilkums	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).