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pro vyhledávání: '"Bathke, Arne"'
Autor:
Carrozzo, Anna Eleonora, Cornelissen, Veronique, Bathke, Arne C., Claes, Jomme, Niebauer, Josef, Zimmermann, Georg, Treff, Gunnar, Kulnik, Stefan Tino
Publikováno v:
In Archives of Physical Medicine and Rehabilitation August 2024 105(8):1498-1505
Akademický článek
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Autor:
Beck, Jonas1 (AUTHOR) jonas.beck@plus.ac.at, Bathke, Arne C.1 (AUTHOR)
Publikováno v:
Statistical Papers. May2024, Vol. 65 Issue 3, p1233-1257. 25p.
We introduce a unified approach to testing a variety of rather general null hypotheses that can be formulated in terms of covariances matrices. These include as special cases, for example, testing for equal variances, equal traces, or for elements of
Externí odkaz:
http://arxiv.org/abs/1909.06205
In applied research, it is often sensible to account for one or several covariates when testing for differences between multivariate means of several groups. However, the "classical" parametric multivariate analysis of covariance (MANCOVA) tests (e.g
Externí odkaz:
http://arxiv.org/abs/1902.10195
When testing for superiority in a parallel-group setting with a continuous outcome, adjusting for covariates (e.g., baseline measurements) is usually recommended, in order to reduce bias and increase power. For this purpose, the analysis of covarianc
Externí odkaz:
http://arxiv.org/abs/1806.03673
Publikováno v:
Statistics in Medicine (2018)
There are many different proposed procedures for sample size planning for the Wilcoxon-Mann-Whitney test at given type-I and type-II error rates $\alpha$ and $\beta$, respectively. Most methods assume very specific models or types of data in order to
Externí odkaz:
http://arxiv.org/abs/1805.12249
Rank-based inference methods are applied in various disciplines, typically when procedures relying on standard normal theory are not justifiable, for example when data are not symmetrically distributed, contain outliers, or responses are even measure
Externí odkaz:
http://arxiv.org/abs/1802.05650
Publikováno v:
In Journal of Statistical Planning and Inference July 2022 219:134-146
It is well known that the standard F test is severely affected by heteroskedasticity in unbalanced analysis of covariance (ANCOVA) models. Currently available potential remedies for such a scenario are based on heteroskedasticity-consistent covarianc
Externí odkaz:
http://arxiv.org/abs/1709.08031