Satellite conference of the International Biometric Conference
2nd-5th July 2014, University of Zurich, Switzerland
Daniela De Angelis, Programme Leader within the ESH: Evidence Synthesis to Inform Health research theme at the MRC Biostatistics Unit, will be an Invited speaker at Bayesian Biostatistics 2014, Satellite conference of the International Biometric Conference.
She will also Chair the Contributed Session on Evidence Synthesis.
There has been much recent interest in Bayesian approaches to collect, analyze and interpret data from biomedical research. Bayesian Biostatistics 2014, a University of Zurich-sponsored and ISBA-endorsed satellite conference of IBC 2014 in Florence, will focus on recent developments in clinical, epidemiological and biological applications of Bayesian methods.
In addition to the invited speakers (list available under scientific programme), they will also have contributed presentations and a poster session. The conference will be a workshop-style meeting covering a range of Bayesian methods and applications in Biostatistics.
- Daniela De Angelis (MRC Biostatistics Unit, Cambridge):
Bayesian inference in infectious disease models: Current challenges
- David Dunson (Duke University):
Bayesian inference on populations of networks
- Andy Grieve (Aptiv Solutions):
How To Test Hypotheses If You Must
- Paul Gustafson (University of British Columbia):
Bayesian inference in partially identified models: Exploring the limits of limited data
- Bhramar Mukherjee (University of Michigan):
Shrinkage methods utilizing auxiliary information to improve prediction models with many covariates
- Beat Neuenschwander (Novartis Pharma AG, Biometrics):
On the Use of Co-Data in Designed Experiments
- Kenneth Rice (University of Washington):
Fixed-effects meta-analysis: it’s what data like to tell you about
- David Rossell (University of Warwick):
Parsimony and prediction accuracy in high-dimensions
- Olli Saarela (McGill University):
Predictive Bayesian inference and dynamic treatment regimes
- Francesco Stingo (MD Anderson):
Bayesian approaches for large biological networks
For further details on Bayesian Biostatistics 2014 click here.