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ALLSTAT  August 2010

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Subject:

SEMINARS: RSS Leeds/Bradford Local Group meeting

From:

Paul Baxter <[log in to unmask]>

Reply-To:

Paul Baxter <[log in to unmask]>

Date:

Tue, 17 Aug 2010 11:10:55 +0100

Content-Type:

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Dear all,

On Wednesday 27th October, the RSS Leeds/Bradford local group will
be hosting an afternoon of talks on "New developments in visualisation"
featuring Roy Ruddle (School of Computing, University of Leeds) and Dean 
Langan (Clinical Trials Research Unit, University of Leeds).

The meeting will be held at the NHS Information Centre, in the Hill and
Diggory rooms on the ground floor, starting at 3pm with refreshments
from 2.30pm.

In accordance with security procedures at the Information Centre, those
attending must pre-register. If you plan to attend, please email Paul
Baxter ([log in to unmask]) by 5pm on Monday 25th October. On
arrival at the Information Centre please go to Reception and ask for the
Royal Statistical Society meeting, you will be collected from there.

Further details can be found on our webpage:

http://tinyurl.com/rss-lba

Regards, Paul
===================================================================
Dr. Paul D. Baxter
Secretary/Treasurer, RSS Leeds/Bradford Local Group,
Division of Biostatistics, University of Leeds, Leeds, LS2 9JT, UK.
-------------------------------------------------------------------
Leeds/Bradford: Wednesday 27 October, 3.00pm, NHS Information Centre.

New developments in visualisation

Roy Ruddle (University of Leeds) [Presentation].

Using "giga-pixel" displays to analyse large data sets

Large, ultra-high resolution computer displays can be built from
commodity hardware, and are colloquially known as "giga-pixel" displays
even though they typically have 50+ million pixels rather than a
billion. We have built four such displays, two installed on the Leeds
University campus and two more at St James' Hospital. In this talk I
will explain what we have learned about the benefits of using giga-pixel
displays to analyse giant images and spatial datasets, in both a
single-user and collaborative (small group) setting.

Dean Langan (University of Leeds) [Presentation].

A range of new graphical ideas for meta-analysis

My work involves the development of a range of graphical ideas based on
the funnel plot. The primary motivation is in light of the recent
introduction of numerous additional features which have become widely
used such as the contour enhanced funnel plot [1] and the pseudo 95%
confidence interval [2]. The popularity of these additional features
suggests that the standard funnel plot is currently not being used to
its full potential.

Such new features all have one aspect in common; they provide a visual
illustration of the impact new studies have on a given meta-analysis.
Specific features include (1) the statistical significance contour; this
feature shows graphically the regions of the funnel plot where one new
study would have to be in order to change the statistical significance
of the meta-analysis based on a predefined significance level. (2) The
heterogeneity contours show how one new study can affect the level of
heterogeneity in a given meta-analysis which could lead to switching
from fixed to a random effects meta-analysis or vice versa. The two
above features and many more have been implemented into meta-analyses
indicating powerful and previously unconsidered interpretations are
possible.

The features within the new graphical framework aim to produce a well
rounded graphical display, capable of illustrating the key components of
meta-analysis effectively such as the distribution of studies, the level
of heterogeneity and presence of bias. From reviewing current graphical
displays in meta-analysis, it is clear that a number of current plots
would be required outside of the new graphical framework. These features
can be used to:

1. Show the current robustness of the meta-analysis.

2. Aide sample size calculations and design prospective similar studies.

3. Help prioritise meta-analyses most in need of an update.

References:

[1]. Peters et al (2008). Contour-enhanced meta-analysis funnel plots
help distinguish publication bias from other causes of asymmetry.
Journal of Clinical Epidemiology 61 991-996

[2]. Stern, J et al (2004). Funnel plots in meta-analysis. The Stata
Journal 4, Number 2, pp. 127-141

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