Bayes 2013

(21 to 23 May)
DAY 1DAY 2DAY 3

Day 1 :

Invited talks

09h00-12h00: Invited speaker: Gianluca Baio, UC London
An introduction to INLA with a comparison to JAGS (hands on)
(including 2 coffee breaks of 15 mins)
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12h00-13h00: Lunch

Invited talks

13h00-14h40: Invited speaker: Pierre Lebrun, Arlenda
An introduction to STAN and SAS PROC MCMC
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14h40-15h00: Coffee break

Contributed talks

15h00-15h20:  T. Jacobs
Modeling in-vitro functional assay of allosteric modulators
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15h20-15h40: E. Rozet et al.
A Bayesian probability criterion to assess analytical results reliability
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15h40-16h00: B. Boulanger and P. Lebrun
A Bayesian model for optimizing the filling of a product to reduce risk of being OOS in presence of uncertainty
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16h00-16h20: J.J. Abellan et al.
Use of conditional power priors to incorporate prior to incorporate prior information in sample size calculations
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Day 2: Presentation of Bayesian applications

 

Invited talks

09h00-10h00: Invited speaker: David Ohlssen, Novartis
Bayesian signal detection in drug research
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10h00-10h40: Invited speaker: Emmanuel Lesaffre and Veronika Rockova, Erasmus MC
Bayesian variable selection with a focus on the analysis of genomic data
Download abstract    Download the slides: Part I | Part II |  Exercice

10h40-11h00: Coffee break

Contributed talks

11h00-11h20: E. Moreno et al.
Bayesian variable selection for identifying subgroups in cost-effectiveness analysis
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11h20-11h40: M. Otava et al.
Bayesian variable selection method for modeling dose-response microarray data under simple order restrictions
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11h40-12h00: J.K. Park et al.
Model selection in Bayesian survival analysis for a multi-country cluster randomized trial
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12h00-13h00: Lunch

Invited
talks

13h00-14h00: Invited speaker: Nicky Best, Imperial College London
Bayesian methods for missing data imputation – Part 1
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14h00-14h40: Invited speaker:  Alexina Mason, Imperial College London
Bayesian methods for missing data imputation – Part 2
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14h40-15h00: Coffee break

Contributed talks

15h00-15h20: N.L. Turner et al.
A Bayesian framework to account for uncertainty due to missing data in meta-analysis
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15h20-15h40: P. Vlachos
Effective Implementation of Bayesian adaptive randomization in early phase clinical development
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15h40-16h00: E. Spaans et al.
Study proposal for a Bayesian adjusted study to investigate the dose of antipsychotics resulting in a target exposure associated with anti-delirant effects with minimized occurrence of side effects
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Day 3: Presentation of Bayesian applications

Contributed talks

09h00-9h20: L.C. Barrado 
Estimation of optimally-combined-biomarker accuracy in the absence of a gold standard reference test
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09h20-9h40: P.E. Verde
Meta-analysis of paired-comparison studies of diagnostic test data: a Bayesian modeling approach
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09h40-10h00: M. Murawska et al.
A comparison between landmarking and joint modeling for producing predictions using longitudinal outcomes
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10h00-10h20: E.-R. Andrinopoulou et al.
Joint modeling of two longitudinal outcomes and competing risk data – Dynamic event predictions
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10h20-10h40: S.R. Bryan et al. 
Bayesian hierarchical modelling of longitudinal glaucomatous visual fields incorporating influential factors
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10h40-11h00: Coffee break

Contributed talks

11h00-11h20: B. Li et al. 
A Bayesian multivariate multilevel Gaussian model with a mixed effects structure in the mean and covariance part
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11h20-11h40: C.M. Russo and D.A. Silva.
Bayesian analysis for heavy-tailed nonlinear mixed effects models
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11h40-12h00: S. Willemsen et al.
A multivariate Bayesian model for human growth
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12h00-12h20: M. Aregay et al.
Hierarchical Bayesian overdispersion models for non-Gaussian repeated measurement data
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12h20-12h30: Farewell

12h30-13h30: Lunch


Complete program in pdf format available here.