We are announcing three short courses, which are scheduled to take place
in October 2009 at the University of Reading, UK. Summary information
is given below. For more detailed information and registration forms
please see http://www.reading.ac.uk/ssc/ providing your address and/or
fax number, or email <mailto:[log in to unmask]>
[log in to unmask]
<mailto:[log in to unmask]> .
Introduction to Survival Analysis
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Dates: 7-9 October 2009. Duration: 3 days. Price: GBP 1005 (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.
This course emphasises the practical aspects of analysing survival data
and interpreting models, but the underlying theory is explained as
appropriate. In practical sessions participants will be able to apply
the methods covered to a simulated clinical trial and to report on the
results. The statistical package SAS will be used to illustrate the
methodologies in the lecture sessions and for practical work. Stata may
also be used for practical work.
General Linear Models
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Dates: 19-20 October 2009. Duration: 2 days. Price: 665 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: 21-23 October 2009. Duration: 3 days. Price: 975 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
Reading University
Reading, UK
Tel: + 44 (0)118 378 8689
Fax: + 44 (0)118 975 8458
Email: [log in to unmask]
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