Christopher Jackson

ESH: Evidence synthesis to inform health
Telephone number: 01223 330381
Email Address:
Other Research Theme Collaborations: COLD

Evidence synthesis in health economic evaluations and public health policy.

Health policies, such as the introduction of new treatments, are commonly evaluated using decision-analytic models. These models combine all relevant evidence from multiple sources, commonly extrapolate it to the long term, and involve a lot of uncertain assumptions. My work involves statistical methods to ensure that the decisions based on these models accurately reflect the available evidence and the extent of uncertainty. Methods for model comparison, flexible modelling and model calibration are used, typically within a Bayesian framework, which allows direct data, indirect data and expert belief to be combined.

Multi-state models for longitudinal data

Multi-state and time-to-event models in health care and disease progression. I maintain the msm R package for continuous-time Markov and hidden Markov modelling.

Statistical computing

Developing and maintaining several R packages, including msm, flexsurv for survival analysis, denstrip for illustrating distributions, ecoreg for ecological inference. Contributing to the OpenBUGS and BRugs software for Bayesian analysis.

Google Scholar profile

Selected Papers