1 citations · 1 across the 2 of their papers we have counts for
5 papers
Adjusted composite likelihood for robust Bayesian meta-analysis
Michele Lambardi di San Miniato, Nicola Sartori
A composite likelihood is a non-genuine likelihood function that allows to make inference on limited aspects of a model, such as marginal or conditional distributions. Composite li…
Accurate inference in negative binomial regression
Euloge Clovis Kenne Pagui, Alessandra Salvan, Nicola Sartori
Negative binomial regression is commonly employed to analyze overdispersed count data. With small to moderate sample sizes, the maximum likelihood estimator of the dispersion param…
Efficient implementation of median bias reduction with applications to general regression models
Euloge Clovis Kenne Pagui, Alessandra Salvan, Nicola Sartori
In numerous regular statistical models, median bias reduction (Kenne Pagui et al., 2017) has proven to be a noteworthy improvement over maximum likelihood, alternative to mean bias…
A New Look at -Tests
Andrew McCormack, Nancy Reid, Nicola Sartori +1
Directional inference for vector parameters based on higher order approximations in likelihood inference has recently been developed in the literature. Here we explore examples of…
Mean and median bias reduction in generalized linear models
Ioannis Kosmidis, Euloge Clovis Kenne Pagui, Nicola Sartori
This paper presents an integrated framework for estimation and inference from generalized linear models using adjusted score equations that result in mean and median bias reduction…