Simultaneous Inference Using Multiple Marginal Models.

ABSTRACT: This tutorial describes single-step low-dimensional simultaneous inference with a focus on the availability of adjusted p values and compatible confidence intervals for more than just the usual mean value comparisons. The basic idea is, first, to use the influence of correlation on the quantile of the multivariate t-distribution: the higher the less conservative. In addition, second, the estimability of the correlation matrix using the multiple marginal models approach (mmm) using multiple models in the class of linear up to generalized linear mixed models. The underlying maxT-test using mmm is discussed by means of several real data scenarios using selected R packages. Surprisingly, different features are highlighted, among them: (i) analyzing different-scaled, correlated, multiple endpoi

SUBMITTER: Hothorn LA 

PROVIDER: S-EPMC11788266 | biostudies-literature | 2025 Jan-Feb

REPOSITORIES: biostudies-literature