Skip Navigation


Biostatistics Advance Access originally published online on July 31, 2009
Biostatistics 2009 10(4):729-743; doi:10.1093/biostatistics/kxp027
This Article
Right arrow Full Text Freely available
Right arrow FREE Full Text (PDF) Freely available
Right arrow Supplementary Material
Right arrowOA All Versions of this Article:
10/4/729    most recent
kxp027v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Disclaimer
Google Scholar
Right arrow Articles by van den Hout, A.
Right arrow Articles by Matthews, F. E.
PubMed
Right arrow PubMed Citation
Right arrow Articles by van den Hout, A.
Right arrow Articles by Matthews, F. E.
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© 2009 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Estimating dementia-free life expectancy for Parkinson's patients using Bayesian inference and microsimulation

Ardo van den Hout* and Fiona E. Matthews

Medical Research Council Biostatistics Unit, Institute of Public Health, Robinson Way, Cambridge CB2 OSR, UK ardo.vandenhout{at}mrc-bsu.cam.ac.uk

* To whom correspondence should be addressed.

Interval-censored longitudinal data taken from a Norwegian study of individuals with Parkinson's disease are investigated with respect to the onset of dementia. Of interest are risk factors for dementia and the subdivision of total life expectancy (LE) into LE with and without dementia. To estimate LEs using extrapolation, a parametric continuous-time 3-state illness–death Markov model is presented in a Bayesian framework. The framework is well suited to allow for heterogeneity via random effects and to investigate additional computation using model parameters. In the estimation of LEs, microsimulation is used to take into account random effects. Intensities of moving between the states are allowed to change in a piecewise-constant fashion by linking them to age as a time-dependent covariate. Possible right censoring at the end of the follow-up can be incorporated. The model is applicable in many situations where individuals are followed over a long time period. In describing how a disease develops over time, the model can help to predict future need for health care.

Keywords: Dementia; Life expectancy; Microsimulation; Multistate model; Random effects; Right censoring; Survival

Received September 11, 2008; revised March 30, 2009; revised May 12, 2009; accepted for publication June 27, 2009.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.