There are many active research projects accessing and applying shared ADNI data. Use the search above to find specific research focuses on the active ADNI investigations. This information is requested annually as a requirement for data access.
| Principal Investigator | |
| Principal Investigator's Name: | james murray |
| Institution: | Newcastle University |
| Department: | Mathematics, Statistics and Physics |
| Country: | |
| Proposed Analysis: | Some 20 years after the first joint models of longitudinal and time-to-event data began to emerge, studies in disease areas such as Alzheimer’s and Parkinson’s disease are now routinely collecting information on multiple longitudinal biomarkers. Such studies present a series of challenges and opportunities. On one hand, this multivariate data is likely to provide predictions that are more informative, and allow for better discrimination between patients. Counter to this are the computational and statistical difficulties in fitting models with multiple biomarkers that often lead, in practice, to the fitting of joint models that either do not take into account the information in all of the biomarkers or adopt unrealistically simple random effects structures in both the longitudinal sub-model and its association with the time-to-event sub-model. Numerical integration methods such as quadrature, Monte Carlo and Laplace approximations have typically been used to fit joint models. This research project will investigate alternative and hybrid approaches to enable fast fitting of multivariate joint models as well as explorations in to reducing the dimensionality of the longitudinal data |
| Additional Investigators |
