Dr. Guillaume Béraud

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Guillaume Béraud defended his PhD thesis last Friday. A job well done! Guillaume will keep working with us on modelling the spread of infectious diseases. A link to his thesis will be made available soon.
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Dr. Yannick Vandendijck

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Yannick Vandendijck has recently been awarded his PhD in Statistics degree from Hasselt University. We are very happy that Yannick will continue to be a member of the SIMID team. Yannick Vandendijck: ‘ Semi-Parametric Methods for Applications in Survey Data and Geostatistical Data’ – 25 September 2015.
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Dr. Steven Abrams

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Steven Abrams has recently been awarded his PhD in Statistics degree from Hasselt University. We are very happy that Steven will continue to be a member of the SIMID team. Steven Abrams: 'Statistical models for estimating individual heterogeneity in acquisition of infectious diseases and outbreak risk in highly vaccinated populations' - 18 September 2015.  
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New FWO postdoctoral fellow: Prof. Dr. Wim Delva

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Wim Delva has been awarded a postdoctoral fellowship by the FWO and will join the SIMID group. His FWO research project is a collaborative project between Hasselt University (Niel Hens) and the KULeuven (Annemie Vandamme), entitled "Combining phylodynamics and agent-based HIV transmission modelling to advance epidemiological methodology and evidence- based public health policies for HIV prevention and treatment"
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Dr. Benson Ogunjimi and Dr. Lander Willem

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Benson Ogunjimi and Lander Willem have recently been awarded their PhD degree. Benson Ogunjimi: 'The quantitative analysis of varicella-zoster virus infection: from epidemiology to immunology' - 27 April 2015 Lander Willem: 'Agent-based models for infectious disease transmission: exploration, estimation & computational efficiency' - 18 June 2015  
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PGEE (with R code)

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We have proposed penalized generalized estimating equations with Elastic Net or L2-Smoothly Clipped Absolute Deviation penalization to simultaneously select the most important variables and estimate their effects for longitudinal Gaussian data when multicollinearity is present. The method is able to consistently select and estimate the main effects even when strong correlations are present. In addition, the potential pitfall of time-dependent covariates is clarified. More info...
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