Salīdzināt metodes

	Robustā atkārtoto mērījumu ANOVA	Frīdmana tests
Nozare	Statistika	Statistika
Saime	Hypothesis test	Hypothesis test
Izcelsmes gads	1990s–2000s	1937
Autors	Rand R. Wilcox	Milton Friedman
Tips	Robust parametric mean comparison	Nonparametric repeated-measures comparison (by ranks)
Pirmavots	Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838	Friedman, M. (1937). The use of ranks to avoid the assumption of normality implicit in the analysis of variance. Journal of the American Statistical Association, 32(200), 675–701.
Citi nosaukumi	robust within-subjects ANOVA, trimmed-mean repeated measures ANOVA, robust RM-ANOVA, heteroscedastic repeated measures ANOVA	Friedman two-way analysis of variance by ranks, Friedman rank test, Friedman Testi
Saistītās	6	2
Kopsavilkums	Robust repeated measures ANOVA tests whether population trimmed means differ across three or more repeated conditions or time points measured on the same subjects. By replacing ordinary means with 20% trimmed means and replacing variances with Winsorized estimates, it maintains acceptable Type I error and power when data are non-normal, skewed, or contain outliers — conditions under which classical repeated measures ANOVA routinely breaks down.	The Friedman test is a nonparametric hypothesis test that compares three or more related conditions measured on the same blocks or subjects, serving as the rank-based alternative to repeated-measures ANOVA. It was introduced by Milton Friedman in 1937 and works on ordinal or continuous data without assuming normality.