Supplementary Material to the paper is provided in Masci, Ieva and Paganoni (2022) and
contains the following three sections. SM-A: Proof of the increasing likelihood property of the …

This paper proposes an innovative statistical method to measure the impact of the
class/school on student achievements in multiple subjects. We propose a semiparametric …

We propose a discrete random effects multinomial regression model to deal with estimation
and inference issues in the case of categorical and hierarchical data. Random effects are …

Evaluating the performance of health care institutions is of paramount interest and it is often
conducted using generalized linear mixed models. In this paper, we focus on the evaluation …

We introduce a novel statistical significance-based approach for clustering hierarchical data
using semi-parametric linear mixed-effects models designed for responses with laws in the …

In the context of clinical and biomedical studies, joint frailty models have been developed to
study the joint temporal evolution of recurrent and terminal events, capturing both the …

Despite their popularity, machine learning predictions are sensitive to potential unobserved
predictors. This paper proposes a general algorithm that assesses how the omission of an …

Traditionally, spline or kernel approaches in combination with parametric estimation are
used to infer the linear coefficient (fixed effects) in a partially linear mixed‐effects model for …

Data are often complex in the sense that they feature dependence between individual
observations, unobserved variables, or highly non-linear and interaction effects. For such …

The present work is performed to propose an innovative model called Semi-Parametric
Generalized Linear Mixed effect Model (SPGLMM), able to uncover subpopulations induced …