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Large Seminar Room, IPH

Institute of Public Health, Forvie Site
Cambridge, CB2 0SR United Kingdom
www.iph.cam.ac.uk

1st Floor, Institute of Public Health

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February 2019

BSU Seminar: “Sample size considerations for the design clinical trials – quantifying the target difference and the target no-difference”

February 21 @ 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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Free

Speaker: Prof Steven Julious, University of Sheffield Title: "Sample size considerations for the design clinical trials - quantifying the target difference and the target no-difference" Abstract: One of the most of the important steps in any clinical trial design is the calculation of the sample size calculation.  From this the study timelines and financial budgets are calculated.  A major driver in the sample size calculation size calculation is the target difference (for a superiority trial) or the target no-difference (for a non-inferiority…

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BSU Seminar: “Optimal Feature Selection using model-based Deep Reinforcement Learning”

February 26 @ 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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Free

Speaker: Dr Konstantina Pallas, Microsoft Title: "Optimal Feature Selection using model-based Deep Reinforcement Learning" Abstract: TBC  

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April 2019

BSU Seminar: “Building Representative Matched Samples with Multi-valued Treatments in Large Observational Studies”

April 11 @ 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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Free

Speaker: Professor Jose Zubizarreta, Harvard University Title: "Building Representative Matched Samples with Multi-valued Treatments in Large Observational Studies" Abstract: In observational studies of causal effects, matching methods are widely used to approximate the ideal study that would be conducted under controlled experimentation. In this talk, I will discuss new matching methods that use tools from modern optimization to overcome five limitations of standard matching approaches. In particular, these new matching methods (i) directly obtain flexible forms of covariate balance, as specified before matching…

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