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Andreea L. Erciulescu: An area-level hierarchical Bayes framework for model-based small area estimation
Model-based small area estimation approaches are in great demand by institutions interested in reliable statistics at disaggregated levels. Such tools overcome estimation challenges using small or incomplete survey data, in part, by combining data from multiple sources. The course starts with an overview of important small area estimation concepts. Area-level models are the main focus of the course, as proven to be of great practical use. Hierarchical Bayes inference is adopted. Software programs are provided for the model fit, validation, prediction, and comparison, with model specification scrips in R STAN. Illustrations use public-use data from the U.S. Census Bureau, for state-level poverty rate estimation research.

Costs:
Developed country - € 80,-
Developing country / Students - € 40,-

AFTER THE REGISTRATION YOU'LL RECEIVE AN INVOICE FROM webinars@isi-web.org. WHEN YOU FINISH THE PAYMENT, YOU'LL BE GRANTED ACCESS TO THE ONLINE COURSE.
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