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Showing 5 out of a total of 5 results for collection: Department of Statistics.
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Bayesian latent time joint mixed effect models for multicohort longitudinal data
Li, D.
;
Iddi, S.
;
Thompson, W.K.
;
Donohue, M.C.
;
for the Alzheimer's Disease Neuroimaging Initiative
(
Statistical Methods in Medical Research
,
2017-11
)
Bayesian latent time joint mixed-effects model of progression in the Alzheimer's Disease Neuroimaging Initiative
Li, D.
;
Iddi, S.
;
Thompson, W.K.
;
Rafii, M.S.
;
Aisen, P.S.
;
Donohue, M.C.
;
Alzheimer's Disease Neuroimaging Initiative
(
Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring
,
2018-08
)
The relative efficiency of time-to-progression and continuous measures of cognition in presymptomatic Alzheimer’s disease
Iddi, S.
;
Li, D.
;
Aisen, P.S.
;
Thompson, W.K.
;
Donohue, M.C.
(
Alzheimer's & Dementia: Translational Research & Clinical Interventions
,
2019-07-18
)
Predicting the course of Alzheimer’s progression
Iddi, S.
;
Li, D.
;
Aisen, P.S.
;
Rafii, M.S.
;
Thompson, W.K.
;
Donohue, M.C.
(
SpringerOpen
,
2019-06-17
)
Estimating the Evolution of Disease in the Parkinson’s Progression Markers Initiative
Iddi, S.
;
Li, D.
;
Aisen, P.S.
;
Rafii, M.S.
;
Litvan, I.
;
Thompson, W.K.
;
Donohue, M.C.
(
Neurodegenerative Diseases
,
2018-08
)
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Author
Donohue, M.C. (5)
Iddi, S. (5)
Li, D. (5)
Thompson, W.K. (5)
Aisen, P.S. (4)
Rafii, M.S. (3)
Alzheimer's Disease Neuroimaging Initiative (1)
for the Alzheimer's Disease Neuroimaging Initiative (1)
Litvan, I. (1)
Subject
Joint mixed-effects models (3)
Latent time shift (3)
Multicohort longitudinal data (3)
Alzheimer’s disease (2)
Disease trajectories (2)
Hierarchical Bayesian models (2)
Alzheimer's disease (1)
Biomakers (1)
Biomarkers (1)
Classification Clinical diagnosis (1)
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Date Issued
2018 (2)
2019 (2)
2017 (1)
Has File(s)
Yes (4)
No (1)