ScholarGate
Асистент

Порівняння методів

Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.

Надійна ANOVA для повторних вимірювань×Стійкий тест Фрідмана×
ГалузьСтатистикаСтатистика
РодинаHypothesis testHypothesis test
Рік появи1990s–2000s1990s–2000s
Автор методуRand R. WilcoxExtension of Friedman (1937); robust variants developed by Wilcox and colleagues
ТипRobust parametric mean comparisonRobust nonparametric repeated measures comparison
Основоположне джерелоWilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838
Інші назвиrobust within-subjects ANOVA, trimmed-mean repeated measures ANOVA, robust RM-ANOVA, heteroscedastic repeated measures ANOVArobust rank-based repeated measures test, trimmed-mean Friedman test, Friedman test with robust estimation, Fried-type robust test
Пов'язані66
ПідсумокRobust 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 robust Friedman test is a nonparametric procedure for comparing three or more related (within-subjects) conditions that replaces standard ranking or mean-based summaries with robust location estimates — typically trimmed means or Winsorized statistics — to reduce the influence of outliers and heavy-tailed distributions on the inference.
ScholarGateНабір даних
  1. v1
  2. 2 Джерела
  3. PUBLISHED
  1. v1
  2. 2 Джерела
  3. PUBLISHED

Перейти до пошуку Завантажити слайди

ScholarGateПорівняння методів: Robust repeated measures ANOVA · Robust Friedman test. Отримано 2026-06-18 з https://scholargate.app/uk/compare