Short Course Information
Online registration for the SAG Statistical Symposium has
closed. There will be on-site registration on a first-come,
first-serve basis. Please note that space in the short courses on
April 6th is limited.
Two half-day short courses will be held on Monday, April 6, 2009.
*CDC and ATSDR Contractors should
register as non-CDC/ATSDR Employees.
This short course will discuss the strengths and limitations of
statistical detection algorithms, with focus on the issues related
to developing, evaluating, and implementing such algorithms in
biosurveillance applications. Open questions to be discussed
include: (1) the appropriate metric or metrics for assessing and
comparing algorithmic performance; (2) the utility of comparing
algorithmic performance on real versus simulated data; (3) how to
best modify existing methods to account for seasonal and other
systematic effects in biosurveillance data; (4) how to maximize
algorithmic detection capabilities within tolerable false positive
rates; and (5) understanding when an electronic biosurveillance
system “adds value” compared to other methods.
This short course will focus on ways to visualize multivariate
and multi-source data when the objective of the analyst is to gain
insights and information about the underlying data processes. A
secondary goal of the course is to discuss techniques to visualize
the results in ways that help convey the concepts to
non-statisticians. Potential topics for the course include
techniques for visualization, such as scatter plot matrices and
smoothing, parallel coordinate plots, Andrews’ curves and images,
choropleth maps, and more. We will also look at ways to find
alternative views of the data and interesting structure via linear
and nonlinear dimensionality reduction and data tours. Finally, the
course will include a discussion of the software tools that one can
use to implement the techniques presented in the course. Where
possible, the examples used to illustrate the techniques will be
data from the health sciences.
