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| Bayesianische ANCOVA× | Robust ANCOVA× | |
|---|---|---|
| Fachgebiet | Statistik | Statistik |
| Familie | Hypothesis test | Hypothesis test |
| Entstehungsjahr≠ | 2012 (formalized; Bayesian general linear models since 1960s) | 1990s–2000s |
| Urheber≠ | Building on Jeffreys (1961) and developed formally for regression/ANCOVA by Rouder & Morey (2012) | Rand R. Wilcox and colleagues |
| Typ≠ | Bayesian parametric covariate-adjusted group comparison | Robust parametric covariate-adjusted comparison |
| Wegweisende Quelle≠ | Rouder, J. N., & Morey, R. D. (2012). Default Bayes factors for model selection in regression. Multivariate Behavioral Research, 47(6), 877–903. DOI ↗ | Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838 |
| Aliasnamen | Bayesian ANCOVA, Bayesian analysis of covariance, B-ANCOVA, Bayesian covariate-adjusted group comparison | robust ANCOVA, heteroscedastic ANCOVA, trimmed-mean ANCOVA, resistant ANCOVA |
| Verwandt≠ | 5 | 4 |
| Zusammenfassung≠ | Bayesian Analysis of Covariance (Bayesian ANCOVA) extends classical ANCOVA by placing prior distributions on group effects and covariate slopes, then updating them with observed data to obtain posterior distributions and Bayes factors. It quantifies evidence for group differences on a continuous outcome after statistically adjusting for one or more continuous covariates, without relying on p-value thresholds. | Robust ANCOVA is a covariate-adjusted group comparison that replaces classical ANCOVA's ordinary least squares estimation with resistant methods — typically trimmed means or M-estimators — so that the test retains valid Type I error control and reasonable power when data contain outliers, heavy-tailed distributions, or heteroscedastic errors. |
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