activity
20072023
most citedCompatibility of Prior Specifications Across Linear Models

40 citations · 89 across the 17 of their papers we have counts for

collaborators

18 papers

stat.ME2023

Assessing replication success via skeptical mixture priors

Guido Consonni, Leonardo Egidi

There is a growing interest in the analysis of replication studies of original findings across many disciplines. When testing a hypothesis for an effect size, two Bayesian approach…

stat.ME2023

Joint structure learning and causal effect estimation for categorical graphical models

Federico Castelletti, Guido Consonni, Marco Luigi Della Vedova

We consider a a collection of categorical random variables. Of special interest is the causal effect on an outcome variable following an intervention on another variable. Condition…

stat.AP2023

Bayesian sample size determination for multi-site replication studies

Konstantinos Bourazas, Guido Consonni, Laura Deldossi

An ongoing "reproducibility crisis" calls into question scientific discoveries across a variety of disciplines ranging from life to social sciences. Replication studies aim to inve…

stat.ME2022★ 14 cited

Bayesian Approaches to Designing Replication Studies

Samuel Pawel, Guido Consonni, Leonhard Held

Replication studies are essential for assessing the credibility of claims from original studies. A critical aspect of designing replication studies is determining their sample size…

stat.ME2022

Bayesian sample size determination for causal discovery

Federico Castelletti, Guido Consonni

Graphical models based on Directed Acyclic Graphs (DAGs) are widely used to answer causal questions across a variety of scientific and social disciplines. However, observational da…

stat.ME2021★ 1 cited

Bayesian graphical modeling for heterogeneous causal effects

Federico Castelletti, Guido Consonni

Our motivation stems from current medical research aiming at personalized treatment using a molecular-based approach. The broad goal is to develop a more precise and targeted decis…