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stat.ME2026
Multivariate mixed models with model-free random effects
Angela Andreella, Livio Finos
Linear mixed models are widely used to analyze non-independent data, but inference for fixed effects can be unreliable under misspecification of the random-effects distribution, in…
stat.ME2024★ 4 cited
Towards a power analysis for PLS-based methods
Angela Andreella, Livio Fino, Bruno Scarpa +1
In recent years, power analysis has become widely used in applied sciences, with the increasing importance of the replicability issue. When distribution-free methods, such as Parti…
stat.ME2024
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…