The Statistical Core serves two functions that are essential for the success of the Einstein Aging Study (EAS). First, the Statistical Core maximizes data quality by implementing a database system that integrates and manages the data collected from the Administrative, Clinical, Neuropathology and Neuroimaging Cores, and from each of the four projects. The Statistical Core assumes responsibility for quality control procedures and for merging data across Projects and Cores. Second, the Statistical Core provides collaborative and consultative support to Project investigators on matters of study design, data analyses and interpretation of results. The Statistical Core is responsible for developing, implementing and interpreting statistical methods appropriate to specific research questions and hypotheses, and it collaborates regulariy with Project investigators on scientific manuscripts.
Specific Aims of the Statistical Core are:
Aim 1. To implement and oversee data procedures to facilitate the seamless exchange of data and ideas among Cores and Projects, and to facilitate data transfer for collaborations with investigators outside the EAS.
Aim 2. To provide a general analytic framework for hypothesis testing, model building and integration of results and analyses across measurement constructs (e.g., exposures, mechanisms, outcomes), and to collaborate with investigators regarding the framing and testing of hypotheses and to provide expertise in the design and conduct of analyses.
Aim 3. To develop new statistical methodology and to apply existing methodology in innovative ways to help to fulfill the other aims of this Core and the Projects and to further aging research in general.
The Statistical Core's contribution to the Program Project is essential and significant because it is needed (1) To ensure a high quality of data;(2) To ensure proper analysis of data for hypothesis testing and hypothesis generation;and (3) To ensure that the data collected in each project and core are optimally utilized for both project specific and cross-project analyses.
|Graff-Radford, Jonathan; Lesnick, Timothy G; Boeve, Bradley F et al. (2016) Predicting Survival in Dementia With Lewy Bodies With Hippocampal Volumetry. Mov Disord 31:989-94|
|Strauss, S B; Kim, N; Branch, C A et al. (2016) Bidirectional Changes in Anisotropy Are Associated with Outcomes in Mild Traumatic Brain Injury. AJNR Am J Neuroradiol :|
|Callisaya, Michele L; Ayers, Emmeline; Barzilai, Nir et al. (2016) Motoric Cognitive Risk Syndrome and Falls Risk: A Multi-Center Study. J Alzheimers Dis 53:1043-52|
|Allen, Mariet; Carrasquillo, Minerva M; Funk, Cory et al. (2016) Human whole genome genotype and transcriptome data for Alzheimer's and other neurodegenerative diseases. Sci Data 3:160089|
|Williams, Kelly L; Topp, Simon; Yang, Shu et al. (2016) CCNF mutations in amyotrophic lateral sclerosis and frontotemporal dementia. Nat Commun 7:11253|
|Ezzati, Ali; Katz, Mindy J; Zammit, Andrea R et al. (2016) Differential association of left and right hippocampal volumes with verbal episodic and spatial memory in older adults. Neuropsychologia 93:380-385|
|Ezzati, Ali; Katz, Mindy J; Lipton, Michael L et al. (2016) Hippocampal volume and cingulum bundle fractional anisotropy are independently associated with verbal memory in older adults. Brain Imaging Behav 10:652-9|
|Carrasquillo, Minerva M; Barber, Imelda; Lincoln, Sarah J et al. (2016) Evaluating pathogenic dementia variants in posterior cortical atrophy. Neurobiol Aging 37:38-44|
|Zammit, Andrea R; Katz, Mindy J; Derby, Carol et al. (2016) Metabolic Syndrome and Smoking Are Associated with Future Development of Advanced Chronic Kidney Disease in Older Adults. Cardiorenal Med 6:108-15|
|Walton, Ronald L; Soto-Ortolaza, Alexandra I; Murray, Melissa E et al. (2016) TREM2 p.R47H substitution is not associated with dementia with Lewy bodies. Neurol Genet 2:e85|
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