Assessing tilavonemab efficacy in early Alzheimer's disease via longitudinal item response theory modeling.

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作者： Xiaoxiao,Zhou ^[1] ; Haotian,Zou ^[1] ; Michael W,Lutz ^[2] ; Konstantin,Arbeev ^[3] ; Igor,Akushevich ^[3] ; Anatoli,Yashin ^[3] ; Kathleen A,Welsh-Bohmer ^[4] ; Sheng,Luo ^[5]

作者单位： Department of Biostatistics & Bioinformatics Duke University Durham North Carolina USA. ^[1] Division of Translational Brain Sciences Department of Neurology Duke University Medical Center Durham North Carolina USA. ^[2] Social Science Research Institute Duke University Durham North Carolina USA. ^[3] Department of Psychiatry Duke University Durham North Carolina USA. ^[4] Duke Clinical Research Institute (DCRI) Duke University Durham North Carolina USA. ^[5]

关键词 bayesian modeling clinimetrics disease progression longitudinal data

DOI 10.1002/trc2.12471

PMID 38835820

发布时间 2024-06-07

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Alzheimer's & dementia (New York, N. Y.)

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Assessing tilavonemab efficacy in early Alzheimer's disease via longitudinal item response theory modeling.

Alzheimer's & dementia (New York, N. Y.)

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Assessing tilavonemab efficacy in early Alzheimer's disease via longitudinal item response theory modeling.

Alzheimer's & dementia (New York, N. Y.)

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Alzheimer's & dementia (New York, N. Y.)

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