4 papers · 1 filter
Bayesian Network Propensity Score to Evaluate Treatment Effects in Observational Studies
Clelia Di Serio, Federica Cugnata, Pier Luigi Conti +4
This paper focuses on the Bayesian Network Propensity Score (BNPS), a novel approach for estimating treatment effects in observational studies characterized by unknown (and likely…
Testing for causal effect for binary data when propensity scores are estimated through Bayesian Networks
Paola Vicard, Paola Maria Vittoria Rancoita, Federica Cugnata +4
This paper proposes a new statistical approach for assessing treatment effect using Bayesian Networks (BNs). The goal is to draw causal inferences from observational data with a bi…
Sequential adaptive strategy for population-based sampling of a rare and clustered disease
Fulvia Mecatti, Charalambos Sismanidis, Emanuela Furfaro
An innovative sampling strategy is proposed, which applies to large-scale population-based surveys targeting a rare trait that is unevenly spread over a geographical area of intere…
A unified principled framework for resampling based on pseudo-populations: asymptotic theory
Pier Luigi Conti, Daniela Marella, Fulvia Mecatti +1
In this paper, a class of resampling techniques for finite populations under complex sampling design is introduced. The basic idea on which it rests is a two-step procedure consist…