Dear Members
Just a note to say that there are only a few places left on the HGLMs workshop on 23rd November in Hemel Hempstead. If you would like to join us then please do not hesitate to contact me to secure your place. The workshop details are included below for your convenience.
with best wishes
Anna F Kane
Training & Customer Support Manager
VSN International Ltd.
ADR: 5 The Waterhouse, Waterhouse Street, Hemel Hempstead HP1 1ES (England)
TEL: +44-(0)1442-450230
FAX: +44-(0)870-1215653
WEB: www.vsni.co.uk
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Hierarchical Generalized Linear Models Workshop with Prof. R. W. Payne, VSNi, Hemel Hempstead, UK. 23 November 2006.
Hierarchical Generalized Linear Models (HGLMs) provide a flexible framework for modelling non-Normal data in situations when there may be several sources of error variation. They are defined by extending the familiar generalized linear models (GLMs) to include additional random terms in the linear predictor. They include generalized linear mixed models as a special case, but do not constrain the additional terms to follow a Normal distribution nor to have an identity link. The methodology also allows for the modelling of the dispersion of the error terms, and leads to an efficient fitting algorithm which does not involve numerical integration.
This workshop, to take place at the VSNi training rooms in Hemel Hempstead, UK on 23rd November 2006, will introduce the underlying theory of HGLM's and discuss case studies illustrating where HGLMs can be useful. It will use the GenStat menu system and procedures developed by Payne, Lee, Nelder and Noh to implement the methodology and to accompany the book on HGLMs by Lee, Nelder & Pawitan* (2006).
Who should attend?
Anyone with an interest in HGLMs or wishing to extend their advanced modelling knowledge.
Pre-requisite skills:
1. A good working knowledge of the GenStat system.
2. Experience of regression and generalized linear models.
Costs:
· £450 (excl. VAT)
For more information or to book your place, please do not hesitate to contact me.
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* Lee, Y., Nelder, J.A. & Pawitan, Y. (2006). Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood. CRC Press.
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