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Lecturer(s)
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Vencálek Ondřej, doc. Mgr. Ph.D.
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Course content
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1) Fixed effects in regression and the motivation for introducing random effects 2) Mixed effects models, interpretation of their parameters 3) Estimation of parameters in mixed effects models 4) Software implementation of mixed effects models
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Learning activities and teaching methods
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unspecified
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Learning outcomes
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understanding of mixed effects models
interpretation of mixed effects models, independent data analysis using mixed effects models
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Prerequisites
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knowledge of basic concepts of probability theory and basics of statistics, especially regression
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Assessment methods and criteria
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unspecified
Credit: active participation in the exercise, solving assigned tasks independently Exam: demonstrate knowledge and understanding of theory and methods
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Recommended literature
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Bates, Douglas, et al. (2014). Fitting linear mixed-effects models using lme4. arXiv preprint arXiv:1406.5823.
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Pinheiro, José; Bates, Douglas. (2006). Mixed-effects models in S and S-PLUS. Springer Science & Business Media.
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Pinherio, José, et al. Package 'nlme'. (2017). Linear and nonlinear mixed effects models. version 3.1.
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