HDR UK Cambridge Seminar Series

HDR UK Cambridge

We are very excited to restart the HDR UK Cambridge Seminar series.  First guest : Professor Bhramar Mukherjee (University of Michigan).

H﻿DR UK Cambridge Seminar Series While sharing the festive cheers w﻿e are very excited to restart H﻿DR UK Cambridge Seminar Series in the new University of Cambridge Heart and Lung Research Institute (HLRI) located at the Addenbrooke&#x27;s site.A﻿ll seminars will be held in a hybrid environment, providing a wonderful opportunity to meet speakers in-person (<a href="https://www.eventbrite.co.uk/e/hdr-uk-cambridge-seminar-series-tickets-472575635447" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">In Person Tickets</a> at the HLRI (0.R088-89 Meeting room) and/or join the exiting discussions virtually. Keeping up the Holiday spirts Brunch - Lunch will be served before the talk (maybe some mince pie too)O﻿ur first guest speaker is Professor Bhramar Mukherjee (University of Michigan)Bhramar Mukherjee is John D Kalbfleisch Collegiate Professor and Chair of Biostatistics at the University of Michigan School of Public Health. She is also a professor of Epidemiology and Global Public Health at the University of Michigan. She is currently a visiting By Fellow at the Churchill College, Cambridge University and a Visiting Scholar at the MRC Biostatistics Unit.Title: Analysis of Genetics linked EHR data: Understanding Selection Bias and Phenotyping Error&quot;In this talk I will share a decade of experience and excitement of being involved with the Michigan Genomics Initiative, a longitudinal biorepository at the University of Michigan Health System, containing administrative healthcare data linked with genetic markers and many other external data sources on nearly 100,000 participants. This is a rich dataset with large p and large n. However, a perioperative recruitment strategy induces selection bias in the analytic sample. In addition, we have an incomplete capture of disease history leading to phenotype misclassification. I will present strategies to understand and reduce bias when these two sources are at play. Examples from COVID-19 and Cancer will be used to illustrate that foundational principles of study design and sampling are critical to turn big data into reliable knowledge.&quot;http://www-personal.umich.edu/~bhramar/ L﻿ooking forward to see you all at 9th of DecemberH﻿DR UK Cambridge

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HDR UK Cambridge Seminar Series

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