Package ‘rema’

Preprint Sep 2026

Quasi-randomization-based inference for multivariate Mann-Whitney effects under random missingness

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. In this paper, we focus on an extensions for repeated measurements and factorial designs subject to randomly missing data. In a previous wor...

Dennis Dobler, Jörg-Tobias Kuhn, L. Amro et al. · 0 citations

Preprint Sep 2026

An absolute measure of heterogeneity for lnOR in meta-analysis

Quantifying the heterogeneity is an important issue in meta-analysis. The conventional heterogeneity statistic, $I^2$, heavily depends on study sample sizes and tends to approach one as the sample sizes increase. To overcome this limitation, a sample size independent measure, ${\rm ICC}_{\rm MA}$, has recently been dev...

Ke Yang, Lei Shi, Wang-Li Xu et al. · 0 citations

Review Open access Sep 2026

Mastering a simulation-based parametric method to obtain bias-corrected point estimates and sampling variance for effect sizes

Meta-analyses require an effect-size estimate and its corresponding sampling variance from primary studies. For some effect size statistics, however, estimators of sampling variance are unavailable, requiring new derivations. Traditionally, such formulas are obtained using hand-derived Taylor expansions (the delta...

S. Nakagawa, Ayumi Mizuno, Coralie Williams et al. · Research Synthesis Methods · 0 citations

Open access 2026

Exploration of Suboptimal Modelling Choices—Ordinal Modelling as a Way to Better Measure Effect Size Heterogeneity?

Heterogeneity in population effect sizes has often been suggested as impairing replication success. The validity of this line of argumentation rests on the assumption that reported heterogeneity estimates provide an accurate description of effect size heterogeneity. However, efforts to precisely measure between-study h...

Maximilian Frank, M. Heene · Collabra: Psychology · 0 citations

Open access Sep 2026

A Neutral Comparison of Multivariate Hypothesis Tests for Parallel Group Designs in Rare Disease Settings

Multivariate endpoints are increasingly used in clinical studies on rare diseases, where sample sizes tend to be small and distributional assumptions are often violated. In such settings, commonly applied parametric multivariate methods, such as classical MANOVA approaches, may suffer from inflated type‐I error or redu...

Martin Geroldinger, M. Laimer, V. Wally et al. · Statistics in Medicine · 0 citations

Open access Aug 2026

Valid Test for Multi-arm Trials with Generalized Linear Models Under Covariate-adaptive Randomization

A new inference method for conducting multiple-treatment comparisons involving endpoints within the generalized linear model (GLM) framework under covariate-adaptive randomization (CAR) that can effectively control Type I error while potentially improving power.

Guannan Zhai, Fei-Fang Hu · Statistica sinica · 0 citations