مقایسهٔ روش‌ها

	تحلیل واریانس عاملی ترکیبی (Mixed ANOVA)	تحلیل واریانس چندمتغیره (MANOVA)	تحلیل واریانس یک‌طرفه	آزمون تی نمونه‌های زوجی
حوزه	آمار	آمار	آمار	آمار
خانواده	Hypothesis test	Hypothesis test	Hypothesis test	Hypothesis test
سال پیدایش	1925	1932	1925	1908
پدیدآور	R. A. Fisher (ANOVA framework); split-plot design formalised in agricultural experimentation	Samuel Stanley Wilks (Wilks' Lambda, 1932); Roy, Hotelling, Pillai (mid-20th c.)	Ronald A. Fisher	Student (W. S. Gosset)
نوع	Parametric factorial ANOVA	Parametric multivariate mean comparison	Parametric mean comparison	Parametric mean comparison (paired)
منبع بنیادین	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	Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd.	Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed.). SAGE. ISBN: 978-1446249185
نام‌های دیگر	split-plot ANOVA, mixed-design ANOVA, between-within ANOVA, Karma ANOVA (Mixed ANOVA — Gruplar Arası × Tekrarlı)	Multivariate ANOVA, Çok Değişkenli ANOVA (MANOVA)	one-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA	dependent samples t-test, repeated measures t-test, matched-pairs t-test, eşleştirilmiş örneklem t-testi
مرتبط	6	5	4	4
خلاصه	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.	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.	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.	The paired samples t-test is a parametric hypothesis test that compares two measurements taken on the same subjects — such as a before and after reading — to decide whether the average change differs from zero. It rests on the t-distribution introduced by Student (W. S. Gosset) in 1908 and works on the within-subject difference scores rather than the raw measurements.