השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| ANOVA למדידות חוזרות רובסטית× | מבחן פרידמן הרובוסטי× | |
|---|---|---|
| תחום | סטטיסטיקה | סטטיסטיקה |
| משפחה | Hypothesis test | Hypothesis test |
| שנת המקור | 1990s–2000s | 1990s–2000s |
| הוגה השיטה≠ | Rand R. Wilcox | Extension of Friedman (1937); robust variants developed by Wilcox and colleagues |
| סוג≠ | Robust parametric mean comparison | Robust nonparametric repeated measures comparison |
| מקור מכונן | Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838 | Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838 |
| כינויים | robust within-subjects ANOVA, trimmed-mean repeated measures ANOVA, robust RM-ANOVA, heteroscedastic repeated measures ANOVA | robust rank-based repeated measures test, trimmed-mean Friedman test, Friedman test with robust estimation, Fried-type robust test |
| קשורות | 6 | 6 |
| תקציר≠ | 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 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. |
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