The International Conference on Multilevel Analysis
SAVE THE DATE and Call for Abstracts
The 14th International Multilevel Conference will be held on March 12-13, 2024.
The conference will be about all aspects of statistical multilevel analysis: innovative applications, theory, software, and methodology. The conference will be in an informal style, with much room for discussion. It will be held in the city centre of Utrecht, within a quarter hour walk or a five-minute bus ride from the Central railway station.
Keynote speakers include dr. Mirjam Moerbeek on sample size calculations and professor Dan McNeish on measurement in intensive longitudinal data. A first pre-conference workshop on extracting personalised latent dynamics using multilevel HMMs is taught by dr. Emmeke Aarts and a second pre-conference workshop on projection predictive variable selection is taught by Dr. Andrew Johnson
Abstract submission
Deadlines for submitting an abstract: If you submit before the 1th of February (2024), you will be notified on the 6th of February if your abstract is accepted.
This edition of the conference will also have the option for researchers working with empirical data to submit posters with questions about their analyses or sampling design. During the conference you will have the opportunity to receive feedback on your (ongoing) research.
Young Researcher Award
The abstracts of four PhD students will be selected and these PhD students will be invited to present their work in a special symposium. The best presentation will be awarded during the closing ceremony with the 'Best PhD Multilevel Presentation Award' and their conference fee will be reimbursed.
Pre-conference workshops
There will be two pre-conference workshop(s) on March 11th. One of these is a workshop on extracting personalised latent dynamics using multilevel HMMs is taught by dr. Emmeke Aarts. A hands-on workshop on projection predictive variable selection for multilevel models using the R-package projpred will be taught by Dr. Andrew Johnson. Andrew will introduce the motivations behind and benefits of projection predictive selection, with an emphasis on practical application and real-world problems. Andrew is a postdoc with Aki Vehtari's group at Aalto University (Helsinki), who are the primary developers and maintainers of the projpred package. Andrew is also part of the development team for Stan, the increasingly popular program for Bayesian analysis.