7 papers · 1 filter
A Standardization Procedure to Incorporate Variance Partitioning Based Priors in Latent Gaussian Models
Luisa Ferrari, Massimo Ventrucci
Latent Gaussian Models (LGMs) are a subset of Bayesian Hierarchical models where Gaussian priors, conditional on variance parameters, are assigned to all effects in the model. LGMs…
A comparison of priors for variance parameters in Bayesian basket trials
Massimo Ventrucci, Alessandro Vagheggini
Phase II basket trials are popular tools to evaluate efficacy of a new treatment targeting genetic alteration common to a set of different cancer histologies. Efficient designs are…
A spectral adjustment for spatial confounding
Yawen Guan, Garritt L. Page, Brian J Reich +2
Adjusting for an unmeasured confounder is generally an intractable problem, but in the spatial setting it may be possible under certain conditions. In this paper, we derive necessa…
PC priors for residual correlation parameters in one-factor mixed models
Massimo Ventrucci, Daniela Cocchi, Gemma Burgazzi +1
Lack of independence in the residuals from linear regression motivates the use of random effect models in many applied fields. We start from the one-way anova model and extend it t…
A unified view on Bayesian varying coefficient models
Maria Franco-Villoria, Massimo Ventrucci, Håvard Rue
Varying coefficient models are useful in applications where the effect of the covariate might depend on some other covariate such as time or location. Various applications of these…
P-spline smoothing for spatial data collected worldwide
Fedele Greco, Massimo Ventrucci, Elisa Castelli
Spatial data collected worldwide at a huge number of locations are frequently used in environmental and climate studies. Spatial modelling for this type of data presents both metho…