We are announcing three short courses, which are scheduled to take place in
October 2007 at The University of Reading, UK. Summary information is given
below. For more detailed information and registration forms please see
www.reading.ac.uk/ssc providing your address and/or fax number, or
email [log in to unmask]
Introduction to Survival Analysis
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Dates: 10 - 12 October 2007. 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.
General Linear Models
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Dates: 15 - 16 October 2007. 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 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 will help
participants understand the ideas involved.
Analysis of Mixed Models
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Dates: 17 - 19 October 2007. 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 data arise are many, and
include clinical trials, industrial applications and environmental
monitoring.
How to fit linear mixed models, and interpret the results, for a range of
common situations is the subject of this course. The MIXED procedure of the
statistical package SAS will be used to illustrate ideas in the lectures and
for hands-on computer practical sessions.
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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