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Introduction to Frequentist and Bayesian mixed (Hierarchical) models (IFBM01)

8 October 2018 - 12 October 2018

Course Overview:

This course will cover introductory mixed or hierarchical modelling (fixed and random effects models) for real-world data sets from both a Frequentist and Bayesian perspective. These methods lie at the forefront of statistics research and are a vital tool in the scientist’s toolbox. The course focuses on introducing concepts and demonstrating good practice in mixed modelling. All methods are demonstrated with data sets which participants can run themselves. Participants will be taught how to fit hierarchical models using both the standard lme4 mixed effects models library in R, together with the Bayesian modelling framework via rstanarm. The course covers the full gamut from simple regression models through to full generalised multivariate mixed structures. The relevant advantages and disadvantages of both the Frequentist and Bayesian approaches will be presented.. Participants are encouraged to bring their own data sets for discussion with the course tutors.

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Introduction to Frequentist and Bayesian mixed (Hierarchical) models (IFBM01)

Details

Start:
8 October 2018
End:
12 October 2018

Venue

PS statistics head office
53 Morrison Street
Glasgow, Scotland G5 8LB United Kingdom
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