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## Folie 1

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### Title: Folie 1 Author: Kristan Schneider Last modified by: Schneider Created Date: 4/5/2007 12:02:08 PM Document presentation format: Bildschirmpr sentation – PowerPoint PPT presentation

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Title: Folie 1

1
Barbara G. Schneider Kristan A.
Schneider
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Hi! Im Barbara
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and Im Kristan
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In the next 5 minutes we will guide you through
our video poster Visualizing Statistical
Inference Using SAS
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teaching statistics to medical students or
physicians is demanding. The reason is that they
are more firmly rooted in applications rather
than in an abstract theoretical framework.
Visualization is an excellent tool to improve
comprehensibility when explaining dry concepts
such as statistical inference.
7
If one desires to draw conclusion from data one
has to be familiar with various statistical
terms, e.g., p-values, significance level, test
statistics, power etc., where at least an
intuitive understanding is required. Our
presentation suggests an approach for teaching
statistical inference using simulated data
together with animated graphics. .
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In particular, the GIFANIM device driver that
facilitates animated graphics is discussed and
the respective SAS code is presented. We address
to everyone who wants to use visualization as a
didactical tool or is interested in the technical
background itself. SAS software refers to
Version 9.1.3.
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Making medical students or physicians understand
statistics is quite a challenge. They are
typically not educated to think in abstract
terms, so visualization is an excellent tool to
obtain more insight on basic but abstract
statistical concepts. Physicians want to draw
conclusions from data.
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Therefore, they have to understand statistical
testing and should be able to interpret output
from statistical software packages. In
particular, the meaning of significance levels,
and the differences between them and p-values are
essential. They must also be aware of power and
the importance of sample size considerations.
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mcvmf
Bridging the gap between physicians real world
and statisticians imaginations, simulations
together with visualization are of great value.
In the following, we demonstrate how to use
visualizations Based on animated graphs to
improve the understanding of the terms mentioned
above.
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When performing any statistical test, all
information of sample values is concentrated in a
single value called realisation (value) of the
test statistic. The test statistic is a random
variable following a specific distribution. To
explain significance level we use a two-sided
one-sample t-test at a significance level of 5.
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We assume that a study is repeated hundred times.
Under the assumption that the null hypothesis
holds, the values of the test statistic can be
associated with dropping dots from the shape of
the corresponding probability density. The next
figures demonstrate this approach using a
t-distribution with 19 degrees of freedom (20
observations per sample). Proc gplot is used to
create the following sequence of images.
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Finally this sequence of images has to be linked
together to produce the animation. Later, we show
how to perform this task using the GIFANIM device
driver.
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But first watch the animation
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To demonstrate power and sample size
considerations we use the one-sided one-sample
z-test. The test should detect a difference of
one third of the standard deviation
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Performing the test with a sample size of 10 and
a significance level of 5 we get these
simulations (blue null hypothesis red
alternative hypothesis).
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A sample size of 75 observations will result in
the following pictures.
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The GIFANIM driver creates GIF animations by
combining images created using SAS/GRAPH. The
driver is controlled by graphics options that
enable you to specify, e.g., delay time,
iteration count, transparency, and disposal
methods..
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The process involved with creating an animated
GIF file requires control of the job sequence and
ensures that the resulting data stream is
constructed properly.
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The GIFANIM data stream consists of three parts
Header, Body, and Trailer. Each of the equally
important Ingredients must be present, to ensure
a properly working animation sequence. For
details we refer to our paper in the proceedings
guide.
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Next, We present the code for the animation.
This is only one possibility, Take this code
as a suggestion.
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Assign the destination for the output file.
Set the graphics environment and assign the
appropriate graphics options for the animation.
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number of studies
These data steps create random numbers and data
for the sequence of graphs
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These data steps create information for the
sequence of graphs
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This data step creates coordinates for the
density functions under both hypotheses
These data steps create coordinates for the dots
and the density function
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The following code sets the symbol statements for
the graphs and uses proc gplot to produce the
series of plots that will be animated by the
GIFANIM driver
To end the animation.
Disassociates the currently assigned filerefs.
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The GIFANIM device driver is of great value for
creating animated graphics in order to improve
your presentations, and to achieve more
attractiveness for the audience.
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• REFERENCES
• SAS/GRAPH 9.1 Reference http//support.sas.com/doc
umentation/onlinedoc/sas9doc.html
• CONTACT INFORMATION
• Barbara Schneider
• Medical University of Vienna
• Section for Medical Statistics
• Spitalgasse 23
• A - 1090 Vienna
• Austria
• barbara.schneider_at_meduniwien.ac.at

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• The end