Methodology Seminar Series
We run seminar series focussing on advanced statistical methods. Over the course of the year, we invite internal and external speakers to present on their areas of expertise and new areas of research.
Recent topics have included
- Dr Aidan O’Keeffe, Department of Statistical Science, University College London. Correlated multi-state models for multiple processes: An application to renal disease progression in systemic lupus erythematosus.
- Dr Ivonne Solis-Trapala, Keele University. Graphical Markov models and recent applications.
- Dr Daniel Farewell, University of Cardiff. Non-ignorable drop out in longitudinal studies.
- Professor Gilbert MacKenzie, University of Limerick. Multi-parameter regression (MPR) survival analysis.
- Dr Michael Crowther, University of Leicester. Parametric multi-state models: Flexible modelling allowing transition-specific distributions with application to estimating clinically useful measures of effect differences.
- Dr Michael Crowther, University of Leicester. Joint modelling of longitudinal and survival data in Stata [one-day course].
- Professor Ian White, University College London. Practical use of multiple imputation to handle missing data [one-day course].
- Dr Karla Hemming, University of Birmingham. Stepped Wedge Trial Designs.
- Professor Gary Collins, University of Oxford. Developing and validating prediction models: issues in methodological conduct and reporting.
- Dr Lisa Hampson, University of Lancaster. Bayesian methods for the design and interpretation of clinical trials in rare diseases.
- Dr Mark Lunt, University of Manchester. How do I recognise an adequate propensity score?
- Dr Rachel Keogh, London School of Hygiene and Tropical Medicine. Estimating casual effects of time-varying exposures using observational data: What can we do using standard regression methods?
- Dr Hayley Jones, Bristol University. Meta-analysis of diagnostic test accuracy across the full range of possible cut-offs.
- Dr Andrew Titman, Lancaster University. Multi-state modelling: an overview.
- Dr Tolu Sajobi, University of Calgary. Latent class item response theory models: a promising approach for characterizing heterogeneity in patient-reported outcomes.