10 citations · 25 across the 15 of their papers we have counts for
15 papers
Quasi-randomization-based inference for multivariate Mann-Whitney effects under random missingness
Dennis Dobler, Jörg-Tobias Kuhn, Lubna Amro +1
Marginal Mann-Whitney effects are widely used across various fields of research, and extensions of this estimand have been developed in many directions in statistical methodology.…
Covariance Correction for Permutation Statistics in Multiple Testing Problems
Merle Munko, Paavo Sattler
In qualitative statistics, permutation tests are very popular, mainly because of their finite-sample exactness under exchangeability. However, in non-exchangeable settings, the cov…
Inference for high dimensional repeated measure designs with the R package hdrm
Paavo Sattler, Nils Hichert
Repeated-measure designs allow comparisons within a group as well as between groups, and are commonly referred to as split-plot designs. While originating in agricultural experimen…
Testing Hypotheses regarding Covariance and Correlation matrices with the R package CovCorTest
Paavo Sattler, Svenja Jedhoff
In addition to the commonly analyzed measures of location, dispersion measurements such as variance and correlation provide many valuable information. Consequently, they play a cru…
Multivariate and Multiple Contrast Testing in General Covariate-adjusted Factorial Designs
Marléne Baumeister, Konstantin Emil Thiel, Lynn Matits +3
Evaluating intervention effects on multiple outcomes is a central research goal in a wide range of quantitative sciences. It is thereby common to compare interventions among each o…
Resampling NANCOVA: Nonparametric Analysis of Covariance in Small Samples
Konstantin Emil Thiel, Paavo Sattler, Arne C Bathke +1
Analysis of covariance is a crucial method for improving precision of statistical tests for factor effects in randomized experiments. However, existing solutions suffer from one or…
Quadratic Form based Multiple Contrast Tests for Comparison of Group Means
Paavo Sattler, Markus Pauly, Merle Munko
Comparing the mean vectors across different groups is a cornerstone in the realm of multivariate statistics, with quadratic forms commonly serving as test statistics. However, when…
Choice of the hypothesis matrix for using the Anova-type-statistic
Paavo Sattler, Manuel Rosenbaum
Initially developed in Brunner et al. (1997), the Anova-type-statistic (ATS) is one of the most used quadratic forms for testing multivariate hypotheses for a variety of different…
Choice of the hypothesis matrix for using the Wald-type-statistic
Paavo Sattler, Georg Zimmermann
A widely used formulation for null hypotheses in the analysis of multivariate -dimensional data is with $\boldsymbol…
Testing for patterns and structures in covariance and correlation matrices
Paavo Sattler, Dennis Dobler
Covariance matrices of random vectors contain information that is crucial for modelling. Specific structures and patterns of the covariances (or correlations) may be used to justif…
Testing Hypotheses about Correlation Matrices in General MANOVA Designs
Paavo Sattler, Markus Pauly
Correlation matrices are an essential tool for investigating the dependency structures of random vectors or comparing them. We introduce an approach for testing a variety of null h…
Inference for high-dimensional split-plot designs with different dimensions between groups
Paavo Sattler, Markus Pauly
In repeated Measure Designs with multiple groups, the primary purpose is to compare different groups in various aspects. For several reasons, the number of measurements and therefo…
Manifold Asymptotics of Quadratic-Form-Based Inference in Repeated Measures Designs
Paavo Sattler
Split-Plot or Repeated Measures Designs with multiple groups occur naturally in sciences. Their analysis is usually based on the classical Repeated Measures ANOVA. Roughly speaking…
Testing Hypotheses about Covariance Matrices in General MANOVA Designs
Paavo Sattler, Arne C. Bathke, Markus Pauly
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…
Inference For High-Dimensional Split-Plot-Designs: A Unified Approach for Small to Large Numbers of Factor Levels
Paavo Sattler, Markus Pauly
Statisticians increasingly face the problem to reconsider the adaptability of classical inference techniques. In particular, divers types of high-dimensional data structures are ob…