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Long Unsupervised

Intermediate: Generalized linear models with random effects (GLMMs & HGLMs) (Genstat_06)


Description
Genstat is a comprehensive statistical system to summarise, display, and analyse data. This course will teach you about its methods to analyse non-Normal data that are subject to several sources of random variation. These occur in many application areas, including medical trials, biological experiments, reliability studies, etc. So, for example, binomial data may arise from counting numbers of infected plants in a field experiment, or from seeing whether patients have been treated successfully in a medical experiment. Poisson data may arise from counting numbers of aphids on leaves, or recording numbers of accident victims in a hospital casualty department, etc. Many of the methods have been developed by statisticians working in agriculture and biology, but they are very widely applicable.

In this course you will learn about
• generalized linear models (brief recap),
• generalized linear mixed models (including the new menus for plots, predictions and permutation tests introduced in the 22nd Edition of Genstat), and
• hierarchical generalized linear models (practice and theory)

The methods will be illustrated using real examples, and there will be practicals so that you can try out the methods and reinforce your understanding.

Prerequisites: You will need some basic Genstat experience − data input, the use of menus, regression and anova etc. It would be helpful if you have also used generalized linear models.

Genstat software: As a participant of this training you have access to a free license for Genstat for the duration of the course, 30 days. Once the course has been purchased you will be sent a license and link to download the software within 24 hours. Please note this will ONLY be sent to the email from which you signed up.

Instructor: Roger Payne

Roger Payne leads the development of Genstat at VSNi, now working part-time after 15 years in the full-time role of VSNi's Chief Science and Technology Officer. He has a degree in Mathematics and a Ph.D. in Mathematical Statistics from University of Cambridge, and is a Chartered Statistician of the Royal Statistical Society. Prior to joining VSNi, Roger was a statistical consultant and researcher at Rothamsted, becoming their expert on design and analysis of experiments, as well as the leader of their statistical computing activities. He originally took over the leadership of Genstat development there in 1985 when John Nelder retired. His other statistical interests include generalized and hierarchical generalized linear models, linear mixed models, the study of efficient identification methods (with applications in particular to the identification of yeasts). Roger's statistical research has resulted in 9 books with commercial publishers, as well as over 100 scientific papers.
Content
  • Session 1
  • Session 1 practise
  • Session 2
  • Session 2 practise
  • Session 3
  • Session 3 practise
  • Session 4
  • Session 4 practise
  • Session 5
  • Session 5 practise
  • Session 6
  • Session 6 practise
  • Session 7
  • Session 8
  • Session 8 practise
  • Session 9
  • Session 9 practise
  • Session 10
  • Session 11
  • Session 11 practise
  • Session 12
  • Session 12 practise
  • Session 13
  • Session 13 practise
  • Conclusions
Completion rules
  • All units must be completed