Sammenlign metoder
Gjennomgå de valgte metodene side om side; rader som avviker, er uthevet.
| Robust ANOVA (Welch & Trimmed Mean)× | Bootstrap-inferens× | Permutasjonstest (Randomiseringstest)× | |
|---|---|---|---|
| Fagfelt | Statistikk | Statistikk | Statistikk |
| Familie | Regression model | Regression model | Regression model |
| Opprinnelsesår≠ | 1951 | 1979 | 2005 |
| Opphavsperson≠ | Welch (1951); robust trimmed-mean approach popularised by Wilcox | Bradley Efron | Good (2005); Edgington & Onghena (2007); resampling tradition |
| Type≠ | Robust one-way analysis of variance | Resampling-based inference | Nonparametric resampling test |
| Opprinnelig kilde≠ | Welch, B. L. (1951). On the comparison of several mean values: an alternative approach. Biometrika, 38(3/4), 330-336. DOI ↗ | Efron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. Annals of Statistics, 7(1), 1-26. DOI ↗ | Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792 |
| Alias≠ | Welch ANOVA, trimmed-mean ANOVA, heteroscedastic one-way ANOVA, Robust ANOVA (Welch & Trimmed Mean) | bootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap Çıkarımı | randomization test, exact permutation test, re-randomization test, Permütasyon Testi |
| Relaterte | 5 | 5 | 5 |
| Sammendrag≠ | Robust ANOVA compares the central tendency of three or more groups when the classical assumptions of normality and equal variances fail. It combines Welch's heteroscedasticity-adjusted statistic, introduced by Welch in 1951, with trimmed-mean tests advanced by Wilcox, giving reliable comparisons in the presence of outliers and unequal group spreads. | Bootstrap inference, introduced by Bradley Efron in 1979, estimates the sampling distribution of a statistic by repeatedly resampling the observed data with replacement. It requires no distributional assumption and produces reliable confidence intervals even in small samples. | The permutation test is a nonparametric resampling procedure that builds the sampling distribution of a test statistic directly from the data by repeatedly shuffling the group labels. Developed in the resampling tradition and treated systematically by Good (2005) and Edgington & Onghena (2007), it requires no parametric distributional assumption and yields an exact p-value. |
| ScholarGateDatasett ↗ |
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