Introduction to Mixed (Hierarchical) models for biologists using R (IMBR01)
Fri, 2018/04/13 - 11:14 — nhoeller
Mixed models, also known as hierarchical models and multilevel models, is a useful class of models for many applied sciences, including biology, ecology and evolution. The goal of this course is to give a thorough introduction to the logic, theory and most importantly implementation of these models to solve practical problems in ecology. Participants are not expected to know mathematics beyond the basic algebra and calculus. Participants are expected to know some R programming and to be familiar with the linear and generalized linear regression. We will be using JAGS (Just Another Gibbs Sampler) for Markov Chain Monte Carlo (MCMC) simulations for analyzing mixed models. The course will be conducted so that participants have substantial hands-on experience.
Start:
Mon, 2018/05/14 - Fri, 2018/05/18
Location:
Orford, Quebec, Canada Mixed models, also known as hierarchical models and multilevel models, is a useful class of models for many applied sciences, including biology, ecology and evolution. The goal of this course is to give a thorough introduction to the logic, theory and most importantly implementation of these models to solve practical problems in ecology. Participants are not expected to know mathematics beyond the basic algebra and calculus. Participants are expected to know some R programming and to be familiar with the linear and generalized linear regression. We will be using JAGS (Just Another Gibbs Sampler) for Markov Chain Monte Carlo (MCMC) simulations for analyzing mixed models. The course will be conducted so that participants have substantial hands-on experience.Intended Audience
Research postgraduates, practicing academics and primary investigators in ecology and evolutionary biology, management and environmental professionals in government and industry.
Venue – Orford Musique, 3165 Chemin du Parc, Orford, QC J1X 7A2, Canada – Google Maps –
Monday 14th: Linear and Generalized linear models
Tuesday 15th: Computational inference
Wednesday 16th: Linear Mixed Models
Thursday 17th: Generalised Linear Mixed Models
Friday 18th: Mixed Models in a Bayesian Framework
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