This repository provides the necessary files to implement dynamic wombling, as described in the manuscript titled Relative rate of change in cognitive score network dynamics via Bayesian hierarchical models reveal spatial patterns of neurodegeneration, available here (insert ePubs link) and published in Statistics in Medicine (DOI 10.1002/sim.8568).
Intention for this repository is to provide the R code to implement dynamic wombling on simulated data, in addition to any Supporting Information for the manuscript.
This repository contains
- The R code for simulation of spatial data according to the methods described in the paper, for 10 ROIs.
- All the R code to run dynamic wombling, as an example.
- Additional visualisation code to reproduce Figure 2 inthe manuscript.
- Supplementary information for the paper.
In the manuscript dynamical wombling was applied on the Alzheimer's disease neuroimaging initiative (ADNI), which is a world-wide data sharing and collaboration for AD research. ADNI is a multisite ongoing longitudinal study designed to develop clinical, imaging, genetic and biochemical biomarkers for Alzheimer's research, whose focus is on early detection and tracking of Alzheimer's disease.
Further information on ADNI, is available here.
As this work is already an extention to brain wombling, any further extension to the dynamical wombling algorith is presented in the Discussion section of the manuscript.
For any information/feedback/bugs or comments on this code or the manuscript, please email: [email protected]