10.5072/FK25H7QRS Rizk-Jackson, Angela 0000-0002-1732-8550 University of California, San Francisco 2013 Aging Cognition Risk-factor Mild Cognitive Impairment Prediction Modeling Center for Imaging of Neurodegenerative Disease 10.5072/j.jalz.2012.05.911 This study replication data resource includes information referencing specific items in the Alzheimer's Disease Neuroimaging Initiative (ADNI) database that were used with the included analysis scripts (R statistical software) to reach conclusions presented in the referenced publication (DOI: 10.1016/j.jalz.2012.05.911). Utilizing the ADNI database, we identified 41 individuals who remained stable for 48-months (NC) and 16 who converted to MCI (CNV). Of these 57 subjects, all had available baseline clinical and MRI data, but only 16 NC and 11 CNV had available FDG-PET data. Wilcoxon Rank Sum tests assessed baseline demographic and clinical imbalances between CNV and NC. The effect of conversion status on neuroimaging measures at baseline was tested using linear regression modeling. Finally, linear discriminant analysis (LDA) models were created using features from an a-priori subset of clinical metrics, MRI measures, and FDG-PET measures obtained at baseline to predict which individuals would later convert to MCI and which would remain stable. We used a leave-one-out cross validation strategy and permutation analysis to confirm significance.