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September 2019

BSU Seminar Series: “Quick & clean: computationally efficient methods for Value of Information measures”

September 17 @ 2:00 pm - 3:00 pm
Large Seminar Room, IPH, Institute of Public Health, Forvie Site
Cambridge, CB2 0SR United Kingdom
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Speaker: Gianluca Baio, UCL   Title: "Quick & clean: computationally efficient methods for Value of Information measures"   Abstract: Recently, there has been much research devoted to developing computationally efficient methods for various measures of the Value of Information in health economics, including the Expected Value of Partial Information (EVPPI) and the Expected Value of Sample Information (EVSI). I will present two sets of methods, one based on computationally efficient Gaussian Process regression based on Integrated Nested Laplace Approximation to…

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October 2019

BSU Short Course: Adaptive Designs and Multiple Testing Procedures for Clinical Trials

October 2 - October 3
Large Seminar Room, IPH, Institute of Public Health, Forvie Site
Cambridge, CB2 0SR United Kingdom
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BSU Short Course: Adaptive Designs and Multiple Testing Procedures for Clinical Trials Dates-Wednesday 2nd – Thursday 3rd October 2019 Course aims: In this course we will give an overview of multiple testing issues and adaptive designs in trials. Participants will learn about a variety of new adaptive clinical trial designs, including multi-arm multi-stage (MAMS), umbrella studies and adaptive randomisation. As well as learning about how to design adaptive trials we will cover the implications of the design on the analysis…

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BSU Seminar Series: “Using sparsity to overcome unmeasured confounding: Two examples”

October 15 @ 2:00 pm - 3:00 pm
Large Seminar Room, IPH, Institute of Public Health, Forvie Site
Cambridge, CB2 0SR United Kingdom
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Speaker: Qingyuan Zhao, University of Cambridge Title: Using sparsity to overcome unmeasured confounding: Two examples Abstract: Sparsity is often used to improve the interpretability of a statistical analysis and/or reduce the variance of a statistical estimator. This talk will explore another aspect—the utility of sparsity in model identifiability through two problems motivated by genetics applications. The first problem is about removing “batch effects” or latent confounders in multiple hypothesis testing. I will present a general framework called Confounder Adjusted Testing…

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BSU Short Course: Introduction to Bayesian Statistics using BUGS

October 23 - October 24
Large Seminar Room, IPH, Institute of Public Health, Forvie Site
Cambridge, CB2 0SR United Kingdom
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Introduction to Bayesian Statistics using BUGS Wednesday 23rd October – Thursday 24th October 2019 Course aims: This course is intended to provide an introduction to Bayesian analysis and MCMC methods, and a fairly detailed tutorial on the use of OpenBUGS/WinBUGS/JAGS. For further course details, please see: Introduction to Bayesian statistics using BUGS To register, click here

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