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

Wednesday 19 September 2018, 12.15PM1.15pm

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:

Thomas Patton
thomas.patton@york.ac.uk
Dina Jankovic
dina.jankovic@york.ac.uk

Economic evaluation seminar dates

  • Wednesday 19 September
    Dr Gianluca Baio, UCL
  • Thursday 18 October
    Dr Han-I Wang,
    Health Sciences, University of York
  • Wednesday 31st October
    Professor Julie Ratcliffe, Adelaide