Paola Vicard

Invited Session
Machine learning in the design, analysis and integration of sample surveys
Organizer: Daniela Marella (Sapienza Università di Roma)
Chair: Chiara Bocci (Università degli Studi Firenze)
Discussant: Fulvia Mecatti (Università degli Studi Milano Bicocca)
Room: T31
Floor: ground
Short summary: Machine learning methods are beginning to be used in various aspects of sample surveys such as weighting, nonresponse and data integration. In this session three main aspects are examined. First of all, the use of Bayesian Networks to deal with the statistical matching problem in a multivariate context is discussed. Next, machine learning techniques incorporating the sampling weights in the imputation process are considered. Finally, a modified version of the PC algorithm for structural learning is proposed to take into account complex sample designs.

Paper
Causal Discovery for complex survey data Author(s)  Paola Vicard
Data Integration without conditional independence: a Bayesian Networks approach Author(s)  Pier Luigi Conti   Paola Vicard   Vincenzina Vitale

Contributed Session
Statistics in Society 2
Chair: Maurizio Carpita (Università di Brescia)
Discussant: Stefania Mignani (Università di Bologna)
Room: T32
Floor: ground

Paper
Bayesian networks as a territorial gender impact assessment tool Author(s)  Lorenzo Giammei   Fulvia Mecatti   Flaminia Musella   Paola Vicard

Contributed Session
Health statistics 1
Chair: Veronica Vinciotti (Università di Trento)
Discussant: Laura Anderlucci (Università di Bologna)
Room: T36
Floor: ground

Paper
Treatment effect assessment in observational studies with multi-level treatment and outcome Author(s)  Pier Luigi Conti   Federica Cugnata   Clelia Di Serio   Fulvia Mecatti   Paola M.V. Rancoita   Paola Vicard