Ardo Van Den Hout
Smooth random change point models
Van Den Hout, Ardo; Muniz-Terrera, Graciela; Matthews, Fiona E.
Authors
Graciela Muniz-Terrera
Professor Fiona Matthews F.Matthews@hull.ac.uk
Pro-Vice-Chancellor Research and Enterprise
Abstract
Change point models are used to describe processes over time that show a change in direction. An example of such a process is cognitive ability, where a decline a few years before death is sometimes observed. A broken-stick model consists of two linear parts and a breakpoint where the two lines intersect. Alternatively, models can be formulated that imply a smooth change between the two linear parts. Change point models can be extended by adding random effects to account for variability between subjects. A new smooth change point model is introduced and examples are presented that show how change point models can be estimated using functions in R for mixed-effects models. The Bayesian inference using WinBUGS is also discussed. The methods are illustrated using data from a population-based longitudinal study of ageing, the Cambridge City over 75 Cohort Study. The aim is to identify how many years before death individuals experience a change in the rate of decline of their cognitive ability. © 2010 John Wiley & Sons, Ltd.
Citation
Van Den Hout, A., Muniz-Terrera, G., & Matthews, F. E. (2011). Smooth random change point models. Statistics in Medicine, 30(6), 599-610. https://doi.org/10.1002/sim.4127
| Journal Article Type | Article |
|---|---|
| Publication Date | Mar 15, 2011 |
| Deposit Date | Dec 8, 2023 |
| Journal | Statistics in Medicine |
| Print ISSN | 0277-6715 |
| Electronic ISSN | 1097-0258 |
| Publisher | John Wiley and Sons |
| Volume | 30 |
| Issue | 6 |
| Pages | 599-610 |
| DOI | https://doi.org/10.1002/sim.4127 |
| Public URL | https://hull-repository.worktribe.com/output/4454918 |