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Alzheimers Dement (Amst). 2019 Jan 11;11:74-84. doi: 10.1016/j.dadm.2018.11.006. eCollection 2019 Dec.

Measuring longitudinal cognition: Individual tests versus composites.

Author information

1
Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
2
Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison WI, USA.
3
Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA.
4
Department of Communication Sciences and Disorders, University of Wisconsin, Madison, WI, USA.
5
Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
6
Department of Medical Physics, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA.
7
Department of Psychiatry, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA.
8
Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.
9
Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.
10
Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK.
11
UK Dementia Research Institute at UCL, London, UK.

Abstract

Introduction:

Longitudinal cohort studies of cognitive aging must confront several sources of within-person variability in scores. In this article, we compare several neuropsychological measures in terms of longitudinal error variance and relationships with biomarker-assessed brain amyloidosis (Aβ).

Methods:

Analyses used data from the Wisconsin Registry for Alzheimer's Prevention. We quantified within-person longitudinal variability and age-related trajectories for several global and domain-specific composites and their constituent scores. For a subset with cerebrospinal fluid or amyloid positron emission tomography measures, we examined how Aβ modified cognitive trajectories.

Results:

Global and theoretically derived composites exhibited lower intraindividual variability and stronger age × Aβ interactions than did empirically derived composites or raw scores from single tests. For example, the theoretical executive function outperformed other executive function scores on both metrics.

Discussion:

These results reinforce the need for careful selection of cognitive outcomes in study design, and support the emerging consensus favoring composites over single-test measures.

KEYWORDS:

Biostatistics; Cognitive aging; Composite scores; Intraindividual variability; Longitudinal data analysis; Neuropsychological tests

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