Whats wrong with 'evidence-based medicine' and how can we do better?

Whats wrong with 'evidence-based medicine' and how can we do better?

By MRC/CSO Social and Public Health Sciences Unit, IHW

Date and time

Fri, 19 Jan 2018 13:00 - 14:00 GMT

Location

McIntyre Building

University Avenue G12 8NN United Kingdom

Description

We are pleased to invite you to:

The Institute of Health and Wellbeing Maurice Bloch Annual Lecture Series 2017/18

Title: Whats wrong with 'evidence-based medicine' and how can we do better?

Presenter: Professor Andrew Gelman

Date: 19 January 2018

Time: 1pm-2pm, a light lunch will be served beforehand

Venue: McIntyre Building room 201

Chair: Dr Jim Lewsey

Abstract:

to follow

Biography

Andrew Gelman is a professor of statistics and political science and director of the Applied Statistics Center at Columbia University. He has received the Outstanding Statistical Application award from the American Statistical Association, the award for best article published in the American Political Science Review, and the Council of Presidents of Statistical Societies award for outstanding contributions by a person under the age of 40. His books include Bayesian Data Analysis (with John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Don Rubin), Teaching Statistics: A Bag of Tricks (with Deb Nolan), Data Analysis Using Regression and Multilevel/Hierarchical Models (with Jennifer Hill), Red State, Blue State, Rich State, Poor State: Why Americans Vote the Way They Do (with David Park, Boris Shor, and Jeronimo Cortina), and A Quantitative Tour of the Social Sciences (co-edited with Jeronimo Cortina).

Andrew has done research on a wide range of topics, including: why it is rational to vote; why campaign polls are so variable when elections are so predictable; why redistricting is good for democracy; reversals of death sentences; police stops in New York City, the statistical challenges of estimating small effects; the probability that your vote will be decisive; seats and votes in Congress; social network structure; arsenic in Bangladesh; radon in your basement; toxicology; medical imaging; and methods in surveys, experimental design, statistical inference, computation, and graphics.


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