[R-sig-Geo] Google Summer of Code proposal on spatial epidemiology with R

Virgilio Gomez Rubio Virgilio.Gomez at uclm.es
Mon Mar 28 23:57:36 CEST 2011


Dear all,

I have submitted a proposal for Google Summer of Code  2011 on spatial
epidemiology. A summary of the proposal is shown below, and full
information (including other proposals for the R Project) can be found
at

http://rwiki.sciviews.org/doku.php?id=developers:projects:gsoc2011

Note that GSoC is only open to students. Those interested in spatial
epidemiology are encouraged to apply. Please, feel free to contact me
off-list if you have any questions. Note that the student application
deadline is on the 8th of April (Friday next week).

Best wishes,

Virgilio


====== DClusterm: Model-based detection of disease clusters

Summary: Model-based detection of disease clusters

Background: The analysis of disease data is important in order to detect
disease outbreaks and links to risk factors. Some of the methods for
cluster detection have been implemented in the DCluster package.
However, a model-based approach would be of interest in order to explore
disease incidence to potential risk factors.

Description: Model-based clustering will be implemented using
Generalized Linear Models (in principle, for Poisson and Binomial
families). Clustering will be modelled as dummy variables (1=area is in
a cluster, 0=area is not is a cluster). Hence, many possible clusters
will be proposed and the most likely cluster will be selected according
to likelihood ratio test, AIC and (possibly) any other reasonable
method.

Skills required: : A good working knowledge of R and Generalized Linear
Models. Some understanding of spatial statistics will be a plus.

Test: Fit a GLM using the North Carolina SIDS data. See
example(“readShapePoly”) in maptools package. In this GLM, SID74 will be
the outcome and BIR74 a covariate; the Poisson family will be used. In
addition, a dummy variable representing a spatial cluster will be
included. This dummy variable will include 5 different contiguous
regions (i.e., the value of this dummy variable will be 1 for these 5
regions and 0 otherwise). Display the residuals of this model in a map.

Mentor: Virgilio Gómez-Rubio, University of Castilla-La Mancha
(Virgilio.Gomez at uclm.es) 



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