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stat.ME2026
Nonparametric methods controlling the median of the false discovery proportion
Jesse Hemerik
When testing many hypotheses, often we do not have strong expectations about the directions of the effects. In some situations however, the alternative hypotheses are that the para…
stat.ME2025
Robust Inference for Generalized Linear Mixed Models: An Approach Based on Score Sign Flipping
Angela Andreella, Jelle Goeman, Jesse Hemerik +1
Despite the versatility of generalized linear mixed models in handling complex experimental designs, they often suffer from misspecification and convergence problems. This makes in…
stat.ME2024
Inference in generalized linear models with robustness to misspecified variances
Riccardo De Santis, Jelle J. Goeman, Jesse Hemerik +2
Generalized linear models usually assume a common dispersion parameter, an assumption that is seldom true in practice. Consequently, standard parametric methods may suffer apprecia…