QANOVA: quantile-based permutation methods for general factorial designs
| Autor: | Marc Ditzhaus, Roland Fried, Markus Pauly |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
FOS: Computer and information sciences
Statistics and Probability Factorial Heteroscedasticity Multivariate statistics Statistischer Test Resampling Population Mathematics - Statistics Theory Median Statistics Theory (math.ST) 01 natural sciences Standard deviation Methodology (stat.ME) 010104 statistics & probability 03 medical and health sciences 0302 clinical medicine Main and interaction effects Statistics FOS: Mathematics 030212 general & internal medicine 0101 mathematics education Statistics - Methodology Mathematics education.field_of_study Birth cohorts IQR Univariate Permutation tests Nichtparametrische Sch��tzung Statistics Probability and Uncertainty Quantile |
| DOI: | 10.17877/de290r-21941 |
| Popis: | Population means and standard deviations are the most common estimands to quantify effects in factorial layouts. In fact, most statistical procedures in such designs are built toward inferring means or contrasts thereof. For more robust analyses, we consider the population median, the interquartile range (IQR) and more general quantile combinations as estimands in which we formulate null hypotheses and calculate compatible confidence regions. Based upon simultaneous multivariate central limit theorems and corresponding resampling results, we derive asymptotically correct procedures in general, potentially heteroscedastic, factorial designs with univariate endpoints. Special cases cover robust tests for the population median or the IQR in arbitrary crossed one-, two- and higher-way layouts with potentially heteroscedastic error distributions. In extensive simulations, we analyze their small sample properties and also conduct an illustrating data analysis comparing children���s height and weight from different countries. TEST;30 |
| Databáze: | OpenAIRE |
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