Address:

MRC Biostatistics Unit,
Institute of Public Health,
University Forvie Site,
Robinson Way,
Cambridge. UK.
CB2 0SR

Telephone Number:

Email Address:

Research Interests:

Health policy makers compare the cost-effectiveness of treatments using decision models. These models extrapolate short-term evidence from trial and hospital data to the long term, and involve a lot of uncertain assumptions. For example, should the incidence of some event be different under each treatment or for different types of patient? These uncertainties are commonly acknowledged by presenting results under different scenarios. But this doesn't clearly tell the decision-maker how plausible each model choice is.

Such choices can often be assessed using the available data, enabling model uncertainty to be accounted for in the decision. This involves statistical methods of model assessment and model averaging. If there are no hard data available, then expert beliefs may be elicited to assess the model choices quantitatively.

Other Research Interests:

Multi-state models for longitudinal data, particularly data arising from disease progression.

I maintain the msm R package for continuous-time Markov and hidden Markov modelling.

Data synthesis. I am a collaborator on the BIAS project at Imperial College London.

Methods for jointly analysing multiple mis-matched datasets in social and environmental epidemiology: particularly aggregate and individual exposure-outcome data.

Selected Recent Publications:

Jackson, C. H., Sharples, L. D. and Thompson, S. G. Structural and parameter uncertainty in Bayesian cost-effectiveness models. Journal of the Royal Statistical Society, Series C.

Jackson, C. H., Thompson, S. G. and Sharples, L. D. Accounting for uncertainty in health economic decision models by using model averaging. Journal of the Royal Statistical Society, Series A (2009) 172(2): 383-404.

Jackson, C. H., Best, N. G. and Richardson, S. Bayesian graphical models for regression on multiple datasets with different variables. Biostatistics (2009) 10(2): 335-351.

Jackson, C. H. Displaying uncertainty with shading. The American Statistician (2008) 62(4): 340-347.

Jackson, C. H., Richardson, S. and Best, N. G. Studying place effects on health by synthesising individual and area-level outcomes. Social Science and Medicine (2008) 67: 1995-2006.

Jackson, C. H., Best, N. G. and Richardson, S. Hierarchical related regression for combining aggregate and individual data in studies of socio-economic disease risk factors. Journal of the Royal Statistical Society, Series A: Statistics in Society 171(1) 159-178 (2008)

Jackson, C. H., Best, N. G. and Richardson, S. Improving ecological inference using individual-level data. Statistics in Medicine (2006) 25(12): 2136--2159

Jackson, C. H. and Sharples, L. D. Models for longitudinal data with censored changepoints. Journal of the Royal Statistical Society, Series C: Applied Statistics (2004) 53(1): 149-162

Jackson, C. H., Sharples, L. D., Thompson, S. G., Duffy, S. W. and Couto, E. Multistate Markov models for disease progression with classification error. Journal of the Royal Statistical Society, Series D: The Statistician (2003) 52(2): 1-17

Jackson, C. H. and Sharples, L. D. Hidden Markov models for the onset and progression of bronchiolitis obliterans syndrome in lung transplant recipients. Statistics in Medicine (2002) 21 113-128.