Salīdzināt metodes

	Jauktais ANOVA	Kovariācijas analīze (ANCOVA)	Daudzvarianto dispersijas analīze (MANOVA)
Nozare	Statistika	Statistika	Statistika
Saime	Hypothesis test	Hypothesis test	Hypothesis test
Izcelsmes gads	1925	1932	1932
Autors	R. A. Fisher (ANOVA framework); split-plot design formalised in agricultural experimentation	Ronald A. Fisher	Samuel Stanley Wilks (Wilks' Lambda, 1932); Roy, Hotelling, Pillai (mid-20th c.)
Tips	Parametric factorial ANOVA	Parametric group comparison with covariate control	Parametric multivariate mean comparison
Pirmavots	Field, A. (2018). Discovering Statistics Using IBM SPSS Statistics (5th ed.). SAGE. ISBN: 978-1526419521	Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574	Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574
Citi nosaukumi	split-plot ANOVA, mixed-design ANOVA, between-within ANOVA, Karma ANOVA (Mixed ANOVA — Gruplar Arası × Tekrarlı)	analysis of covariance, covariance analysis, ANCOVA (Kovaryans Analizi)	Multivariate ANOVA, Çok Değişkenli ANOVA (MANOVA)
Saistītās	6	4	5
Kopsavilkums	Mixed ANOVA is a parametric factorial analysis of variance that simultaneously examines at least one between-subjects factor and at least one within-subjects (repeated-measures) factor. Rooted in R. A. Fisher's ANOVA framework formalised in 1925, it is the standard method for experimental and longitudinal designs in which different groups are each measured across multiple time points or conditions.	ANCOVA is a parametric hypothesis test that compares the adjusted means of two or more independent groups while statistically controlling for one or more continuous covariates. By removing the portion of outcome variance explained by the covariate, ANCOVA increases statistical precision and produces fairer group comparisons. The method builds on the general linear model framework consolidated by Fisher in the early 1930s and is described comprehensively by Tabachnick and Fidell (2013).	MANOVA is a parametric hypothesis test that simultaneously compares group means across multiple continuous dependent variables, controlling the inflation of Type I error that would result from running separate ANOVAs. Key multivariate test statistics — Wilks' Lambda, Pillai's Trace, Hotelling-Lawley Trace, and Roy's Greatest Root — were developed between the 1930s and 1950s, with Wilks' Lambda formalised by Samuel Stanley Wilks in 1932.