Accessibility statement

Quick & clean: computationally efficient methods for Value of Information measures

Wednesday 19 September 2018, 12.15PM to 1.15pm

Speaker(s): Dr Gianluca Baio, UCL

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 compute the EVPPI and the other based on "moment-matching" to compute the EVSI. Both methods draw on existing methodologies but expand them by providing general-purpose algorithms that can be applied on a wide range of real-life modelling structures. I will present the methods using toy and real-life examples and discuss their advantages and limitations with respect to applicability in practice.

Location: Alcuin A Block A019/20

Who to contact

For more information on these seminars, contact:
Alfredo Palacios
Shainur Premji

If you are not a member of University of York staff and are interested in attending a seminar, please contact 
so that we can ensure we have sufficient space

Economic evaluation seminar dates

  • Thursday 17 January
    Edward Cox, CHE, University of York
  • Thursday 21 February
    Sebastian Hinde, CHE, University of York
  • Thursday 21 March
    Alessandro Grosso, CHE, University of York