We are re-announcing three short courses, which are taking place in
October 2006 at The University of Reading, UK. Summary information is given
below. For more detailed information and registration forms please see
http://www.ssc.rdg.ac.uk providing your address and/or fax number, or email
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Fitting General Linear Models
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Dates: 9 - 10 October 2006. Duration: 2 days. Price: 585 GBP.
General Linear Models (GLMs) form a unified underlying theory that covers
simple and multiple linear regression techniques and general analysis of
variance procedures for balanced and unbalanced data. An essential
feature is the use of a normally distributed residual or error term.
This course will briefly present the theory of general linear models and
discuss their application and interpretation in problems of agriculture,
biological and medical sciences and in pharmaceutical work. Many examples
will be used to illustrate a wide range of GLMs. Practical sessions,
based on SAS or GenStat will help participants understand the ideas
involved.
Analysis of Mixed Models
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Dates: 11 - 13 October 2006. Duration: 3 days. Price: 855 GBP.
Mixed Models have both fixed and random effects. Such models arise when
treatments are a random selection from a wider group and when data are
collected from a multi-strata structure with different levels of
variability.
Practical situations where such experimental data arise are many. For
example, in a clinical trial to evaluate the effectiveness of two drugs, the
drugs may be administered to patients from a random selection of hospitals
with a view to generalising the conclusions to patients from all hospitals.
In environmental studies, random locations with randomly selected sites may
be measured for soil and environmental characteristics. Models for such
situations will be fitted using the SAS MIXED procedure. Interpretation of
MIXED output will be covered in lectures and computer practical sessions.
Introduction to Survival Analysis
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Dates: 18 - 20 October 2006. Duration: 3 days. Price: 885 GBP (includes
textbook).
Survival data arise in a literal form from trials concerning
life-threatening conditions, but the methodology can also be applied to
other waiting times such as the duration of pain relief. This course
discusses both the design and analysis of clinical trials in which the
response variable is a survival time.
During lectures the statistical package SAS will be used to illustrate the
methodologies, and in practical sessions participants will analyse and
report on the results of a simulated clinical trial. Considerable emphasis
is placed on practical work using SAS and the interpretation of models, but
some underlying theory will also be explained as appropriate. Stata may
also be used for practical work.
Julia Harris
Short Course Administrator
Statistical Service Centre
Tel: + 44 (0)118 378 8689
Fax + 44 (0)118 975 3169
email: [log in to unmask]
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