The Biostatistics Core (Core C) will bridge the transition from the DIAN database stored and managed by the Informatics Core (Core H) to the analyses of the longitudinal data within, between, and among the various data domains, the latter of which serves as the primary responsibility of the Core. Specifically the Biostatistics Core will: (1) oversee the statistical quality control of data for the study and produce appropriately de-identified and statistically analyzable datasets for distribution/analysis;(2) lead the statistical data analyses and collaborate in report preparation for all Cores and projects, and consult on the design of all projects and on the application of appropriate statistical and methodological techniques;(3) develop and implement appropriate statistical models for longitudinal changes in potential markers and use these models to test the statistical hypotheses about the preclinical changes of AD and about the temporal difference on preclinical changes of AD among various markers, and (4) serve as an advisory group for other researchers interested in using the DIAN database for additional analyses. The Biostatistics core will achieve these specific aims through extensive interactions and collaborations with all other components of DIAN.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01AG032438-02
Application #
7880564
Study Section
Special Emphasis Panel (ZAG1)
Project Start
Project End
Budget Start
2009-07-01
Budget End
2010-06-30
Support Year
2
Fiscal Year
2009
Total Cost
$56,760
Indirect Cost
Name
Washington University
Department
Type
DUNS #
068552207
City
Saint Louis
State
MO
Country
United States
Zip Code
63130
Lee, Seonjoo; Zimmerman, Molly E; Narkhede, Atul et al. (2018) White matter hyperintensities and the mediating role of cerebral amyloid angiopathy in dominantly-inherited Alzheimer's disease. PLoS One 13:e0195838
Xiong, Chengjie; Luo, Jingqin; Chen, Ling et al. (2018) Estimating diagnostic accuracy for clustered ordinal diagnostic groups in the three-class case-Application to the early diagnosis of Alzheimer disease. Stat Methods Med Res 27:701-714
Jacobs, Heidi I L; Hedden, Trey; Schultz, Aaron P et al. (2018) Structural tract alterations predict downstream tau accumulation in amyloid-positive older individuals. Nat Neurosci 21:424-431
Gabel, Matthew; Gooblar, Jonathan; Roe, Catherine M et al. (2018) Political Ideology, Confidence in Science, and Participation in Alzheimer Disease Research Studies. Alzheimer Dis Assoc Disord 32:179-184
Twohig, Daniel; Rodriguez-Vieitez, Elena; Sando, Sigrid B et al. (2018) The relevance of cerebrospinal fluid ?-synuclein levels to sporadic and familial Alzheimer's disease. Acta Neuropathol Commun 6:130
Joseph-Mathurin, Nelly; Su, Yi; Blazey, Tyler M et al. (2018) Utility of perfusion PET measures to assess neuronal injury in Alzheimer's disease. Alzheimers Dement (Amst) 10:669-677
Oxtoby, Neil P; Young, Alexandra L; Cash, David M et al. (2018) Data-driven models of dominantly-inherited Alzheimer's disease progression. Brain 141:1529-1544
Chhatwal, Jasmeer P; Schultz, Aaron P; Johnson, Keith A et al. (2018) Preferential degradation of cognitive networks differentiates Alzheimer's disease from ageing. Brain 141:1486-1500
Franzmeier, Nicolai; Düzel, Emrah; Jessen, Frank et al. (2018) Left frontal hub connectivity delays cognitive impairment in autosomal-dominant and sporadic Alzheimer's disease. Brain 141:1186-1200
Allison, Samantha; Babulal, Ganesh M; Stout, Sarah H et al. (2018) Alzheimer Disease Biomarkers and Driving in Clinically Normal Older Adults: Role of Spatial Navigation Abilities. Alzheimer Dis Assoc Disord 32:101-106

Showing the most recent 10 out of 108 publications