Dear all,
we are glad to inform you that it is now possible to pay the registration fee (by bank transfer or credit card) for the Applied Bayesian Statistics ABS23 which will be held in Firenze (Italy) on June, 12-16, 2023.
Website: http://www.mi.imati.cnr.it/conferences/abs23/
The school is organised by CNR IMATI (Institute of Applied Mathematics and Information Technologies at the Italian National Research Council in Milano), this year in cooperation with the Florence Center for Data Science and the
Department of Statistics, Computer Science and Applications at the University of Firenze.
The topic will be BAYESIAN CAUSAL INFERENCE.
The lecturer will be FAN LI (Duke University, https://scholars.duke.edu/person/fli) with the support by researchers at the
University of Firenze.
The University of Firenze can issue a certificate stating that the course is worth 3 ECTS credits. Interested students can write to abs23@mi.imati.cnr.it
Once you register on the school website:
http://www.mi.imati.cnr.it/conferences/abs23/
you will receive an email with the link to pay by credit card as well as the information on payment by bank transfer (please note that the early registration fee is available until April, 15th, 2023).
Please note that only a very limited number of seats is still available and that Firenze is a very popular tourist place, so that it is better to make arrangements as soon as possible. More details about accommodation are available in the ABS23 website.
As in the past (since 2004), there will be a combination of theoretical and practical sessions, along with presentations by participants about their work (past, current and future) related to the topic of the school.
OUTLINE: The aim of this course is to introduce the fundamental concepts and the state-of-the-art methods for causal inference under the potential outcomes framework, with an emphasis on the Bayesian inferential paradigm.
Topics will cover randomized experiments, common methods for observational studies, such as propensity score, matching, weighting and doubly-robust estimation, heterogeneous treatment effects, sensitivity analysis,
instrumental variables, principal stratification, panel data methods, and longitudinal treatments. Recent advances related to high dimensional analysis and machine learning will be naturally incorporated into the discussion. All methods will be illustrated via real world case studies.
We hope you will be interested in the school and we would like to meet you in Firenze next year. We invite you also to share the information with people potentially interested.
Best regards
Elisa Varini and Fabrizio Ruggeri
Executive Director and Director of ABS23