Apologies for cross-posting

Mixed effects modelling course, 8 - 11 December 2009. Newburgh, UK

5 remaining places

When: Tuesday 8 December until Friday 11 December 2009
Where: Conference room in the Newburgh Golf Course

Program. Tuesday: Generalised least squares to deal with heterogeneity in linear regression and additive models. Wednesday and Thursday: Mixed effects models to deal with 1-way and 2-way nested data. Friday: Adding temporal and spatial correlation structures to mixed effect models, additive models and linear regression models. We will cover Chapters 4 to 7 and various case study chapters from Zuur et al. (2009). Mixed effects models and extensions in ecology with R. (2009).

Costs: 550 GBP + 15% VAT
The course fee includes tea/coffee in the morning and afternoon, and a light lunch (sandwiches + soup). The course fee does not include a copy of the book, and no photocopies will be provided. Hence, you need to buy the book before the course, or we can provide a book for 45 GBP.

Pre-required knowledge: Linear regression (as in Appendix A from Zuur et al (2009) or Chapter 5 in Zuur et al (2007). Basic R skills. Additive modelling (as in Chapter 7 of Zuur et al. 2007).
Course times: 09.30 - 17.00
This is a non-technical course.

Further info: http://www.highstat.com/




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Dr. Alain F. Zuur
First author of:

1. Analysing Ecological Data (2007).
Zuur, AF, Ieno, EN and Smith, GM. Springer. 680 p.
URL: www.springer.com/0-387-45967-7


2. Mixed effects models and extensions in ecology with R. (2009).
Zuur, AF, Ieno, EN, Walker, N, Saveliev, AA, and Smith, GM. Springer.
http://www.springer.com/life+sci/ecology/book/978-0-387-87457-9


3. A Beginner's Guide to R (2009).
Zuur, AF, Ieno, EN, Meesters, EHWG. Springer
http://www.springer.com/statistics/computational/book/978-0-387-93836-3


Other books: http://www.highstat.com/books.htm


Statistical consultancy, courses, data analysis and software
Highland Statistics Ltd.
6 Laverock road
UK - AB41 6FN Newburgh
Tel: 0044 1358 788177
Email: highs...@highstat.com
URL: www.highstat.com
URL: www.brodgar.com

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