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International cooperation and technology transfer
Mussio, Luigi

cause GeoMed incorporates the methods of
Stat!); but GeoMed goes beyond Stat!, pro
viding a broader range of spatial statistics in
• Cuzick and Edwards’s test
• Grimson’s Method
• Ripley’s K-function
• Besag and Newell’s Test
• Local Indicators of Spatial Autocorrelation
• Turnbull’s Test
• Kulldorff’s Spatial Scan Statistic
• Bithell’s Test
• Diggle’s method
• Score test of Lawson and Waller
For each of the many tests and methods above
we provide an on-line Information Frame, or
succinct textual and graphical description of
the test: this takes a user from description of
the statistic, to the null and alternative hy
potheses, to an example analysis using the
statistic. These tests are also linked together
by the statistical advisor, which serves as an
aid to a researcher in choosing the appropriate
test given their particular statistical problem.
Ultimately GeoMed software will be available
for download from our web site; in the mean
time other statistical software (e.g. Stat! and
Gamma) is available in demo versions from
the web site.
5 Our Course
We now describe our course in some detail.
This will serve to illustrate how one might use
the resources which are currently in place for
the development of a course of one’s own.
The University of Michigan is involved in
the GeoMed project because members of the
University wish to see their students well-
educated in some of the latest techniques for
spatial analysis: we thus strive to see that
these student needs are met. We focus on the
course because it serves as the center around
which we continue to build the web site; but
we consider that the web site has broader ob
jectives than the course (we see our course as a
specific imlementation of the materials avail
able at the web site).
5.1 Objectives and Audience
The course objective is as follows: To pro
vide students with the knowledge, theory, and
methodological skills for analyzing and inter
preting the spatial patterns of various diseases
in order to elucidate underlying exposure pro
cesses giving rise to the observed patterns. The
students referred to are expected to have a
special interest in Public Health, and recruit
ment for this new course especially targets
students in the School of Public Health. This
includes especially students from the depart
ments of Biostatistics and Epidemiology, at
both the PhD level and the Masters level.
Students are expected to have had introduc
tory probability theory and to have some basic
knowledge of biostatistics.
Another objective is to exercise certain
BioMedware software products, including one
established product (Stat! [5]), a product soon
to be released (Gamma [1]), and especially the
new software designed for this project (which
we call GeoMed [2]). This last piece of soft
ware will serve as the keystone for much of
the spatial statistical analysis we do in our
course in the future. Several computer labs
have been structured around these pieces of
software, each of which is designed for per
forming spatial statistical tests. The course
allows us to both alpha/beta test the soft
ware, and to generate insight from the stu
dents about ways in which the software can
be improved.
5.2 Modular Design
From a logistical standpoint, we have 24 hours
of lecture time, divided into two-hour blocks
in which to meet our objectives, along with
another 24 hours of lab (again in two-hour
blocks). We focus on seven basic ideas:
• Introductory epidemiological concepts (1