Estimating long‐term multivariate progression from short‐term data
Abstract
Diseases that progress slowly are often studied by observing cohorts at different stages of disease for short periods of time. The Alzheimer's Disease Neuroimaging Initiative (ADNI) follows elders with various degrees of cognitive impairment, from normal to impaired. The study includes a rich panel of novel cognitive tests, biomarkers, and brain images collected every 6 months for as long as 6 years. The relative timing of the observations with respect to disease pathology is unknown. We propose a general semiparametric model and iterative estimation procedure to estimate simultaneously the pathological timing and long‐term growth curves. The resulting estimates of long‐term progression are fine‐tuned using cognitive trajectories derived from the long‐term “Personnes Agées Quid” study.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Mar 24, 2014
- Source ID
- 10.1016/j.jalz.2013.10.003
Entities
People
- Anthony C. Gamst
- Clifford Jack
- Hélène Jacqmin‐gadda
- Jean‐françois Dartigues
- Laurel A. Beckett
- Michael C. Donohue
- Michael W. Weiner
- Mélanie Le Goff
- Paul S. Aisen
- Rema Raman
- Ronald G. Thomas
Organizations
- French National Institute of Health and Medical Research
- Mayo Clinic
- National Institutes of Health
- University of California, San Diego
- University of California, San Francisco