University of Cambridge > Talks.cam > MRC Biostatistics Unit Seminars > Virtual BSU Seminar: "Using Variational Bayes for fast inference in large longitudinal datasets”

Virtual BSU Seminar: "Using Variational Bayes for fast inference in large longitudinal datasets”

Add to your list(s) Download to your calendar using vCal

  • UserDr David Hughes, Institute of Population Health, University of Liverpool
  • ClockTuesday 01 February 2022, 14:00-15:00
  • HouseVirtual Seminar .

If you have a question about this talk, please contact Alison Quenault.

This will be a free virtual seminar. If you would like to attend, please register here: https://www.eventbrite.co.uk/e/bsu-virtual-seminar-dr-david-hughes-tickets-242962345917

Collecting information on multiple longitudinal outcomes is increasingly common in many clinical settings. In many cases it is desirable to model these outcomes jointly. However, in large datasets, with many outcomes, computational burden often prevents the simultaneous modelling of multiple outcomes within a single model. We develop a mean field variational Bayes algorithm, to jointly model multiple Gaussian, Poisson or binary longitudinal markers within a multivariate generalised linear mixed model. Through simulation studies and clinical applications (in the fields of sight threatening diabetic retinopathy and primary biliary cirrhosis) we demonstrate substantial computational savings of our approximate approach when compared to a standard Markov Chain Monte Carlo, while maintaining good levels of accuracy of model parameters.

This talk is part of the MRC Biostatistics Unit Seminars series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.

 

© 2006-2022 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity