| EPSRC Reference: |
GR/R71948/01 |
| Title: |
Modelling cancer incidence and morality : new models for analysing trends and making projections |
| Principal Investigator: |
Wright, Professor D |
| Other Investigators: |
|
| Researcher Co-Investigators: |
|
| Project Partners: |
|
| Department: |
Sch of Computing & Mathematics |
| Organisation: |
University of Plymouth |
| Scheme: |
Fast Stream |
| Starts: |
01 October 2002 |
Ends: |
30 September 2005 |
Value (£): |
47,140
|
| EPSRC Research Topic Classifications: |
| Bioinformatics |
Medical science & disease |
| Statistics & Appl. Probability |
|
|
| EPSRC Industrial Sector Classifications: |
| No relevance to Underpinning Sectors |
|
|
| Related Grants: |
|
| Panel History: |
|
|
Summary on Grant Application Form |
|
Statistical models for cancer registry data can provide useful insights into the epidemiology of cancer and can also be used to make projections of future rates. The aim of this research is to make projections of cancer incidence and mortality for a wide range of sites and countries, and to further develop current methodology to make more efficient use of available data. The research will use Bayesian age-period-cohort models. Extrapolating classical estimates of age, period and cohort effects requires the analyst to make certain subjective decisions (see, for example, Osmond, 1985). Recent developments in computer-intensive methods have enabled Bayesian approaches to be applied, with the advantage that rates can be projected without making parametric assumptions about future period and cohort effects. Instead, non-parametric smoothing models are incorporated in the modelling procedure to reduce variation and make more robust projections (Berzuini and Clayton, 1994). Using this approach the uncertainty associated with making projections can be readily explored. Using computer-intensive simulation methods, the models will be extended to deal with missing data, data collected in unequal time bands and coarsened data. In particular we consider mortality data, available for individual calendar years but traditionally analysed in 5-year intervals. Technical implemention issues will also be considered.
|
|
Key Findings |
|
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
|
Potential use in non-academic contexts |
|
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
|
Impacts |
|
| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
|
| Date Materialised |
|
|
|
|
Sectors submitted by the Researcher |
|
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
| Project URL: |
|
| Further Information: |
|
| Organisation Website: |
http://www.plym.ac.uk |