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Förslaget inkom 2004-12-09

Methods to control for confounding variables in screening for associations in the WHO drug safety database

OBS! ANSÖKNINGSTIDEN FÖR DETTA EXJOBB HAR LÖPT UT.
The WHO Collaborating Centre for International Drug Monitoring in Uppsala (also known as the Uppsala Monitoring Centre) holds the world's largest database of spontaneously reported adverse drug reaction (ADR) incidents. The database currently consists of over 3 million reports from more than 70 countries all over the world and around 200,000 new reports are added each year. To help in the on-going analysis of this massive data set, a method for data mining referred to as IC analysis has been developed to screen for associations in large databases. This is a high profile project that has been reported on for example in Dagens Nyheter (14/5 1998) and Microsoft magazine (nr 2, 1998).

The heterogeneity of the WHO database may lead to problems with confounding (when ancillary variables distort the apparent relationship under study). The aim of this Master's thesis project will be to study the impact of confounding variables in IC analysis on the WHO database and to propose a strategy for how to handle this issue in practice - i.e. when to carry out stratified analyses and how to select the variables to stratify by.

The successful applicant should be a last year student of engineering (civilingenjörsprogram) or mathematical statistics. She or he should have a great interest in mathematical statistics and methods for knowledge discovery in databases, especially as applied to real world problems. Some programming skills are required as all proposed methods are to be implemented and evaluated in practice (we use Matlab for research projects). Both research and development is carried out in a Linux environment, and the official language for the project is English.

For more information or to apply (include CV), please contact:

Niklas Norén
Research Engineer
Data Mining Development

Uppsala Monitoring Centre
Stora torget 3
753 20 UPPSALA

at:
[email protected]
018-656067

or at:
[email protected]
08-164560
(Mathematical Statistics
Stockholm University)


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