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Latent Factor Structure and Measurement Invariance of the NIH Toolbox Cognition Battery in an Alzheimer’s Disease Research Sample

Published online by Cambridge University Press:  05 October 2020

Yue Ma Open the ORCID record for Yue Ma [Opens in a new window] ,
Cynthia M. Carlsson ,
Michelle L. Wahoske ,
Hanna M. Blazel ,
Richard J. Chappell ,
Sterling C. Johnson ,
Sanjay Asthana  and
Carey E. Gleason
Yue Ma*
Affiliation:
Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, J5/1 Mezzanine, 600 Highland Avenue, Madison, WI 53792, USA
Cynthia M. Carlsson
Affiliation:
Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, J5/1 Mezzanine, 600 Highland Avenue, Madison, WI 53792, USA Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, 610 Walnut Street, 9th Floor, Madison, WI 53726, USA Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, 2500 Overlook Terrace, Madison, WI 53705, USA
Michelle L. Wahoske
Affiliation:
Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, J5/1 Mezzanine, 600 Highland Avenue, Madison, WI 53792, USA
Hanna M. Blazel
Affiliation:
Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, J5/1 Mezzanine, 600 Highland Avenue, Madison, WI 53792, USA
Richard J. Chappell
Affiliation:
Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, J5/1 Mezzanine, 600 Highland Avenue, Madison, WI 53792, USA Department of Biostatistics and Medical Informatics, University of Wisconsin, WARF Room 201, 610 Walnut Street, Madison, WI 53726, USA Department of Statistics, University of Wisconsin, 1300 University Avenue, Madison, WI 53706, USA
Sterling C. Johnson
Affiliation:
Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, J5/1 Mezzanine, 600 Highland Avenue, Madison, WI 53792, USA Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, 610 Walnut Street, 9th Floor, Madison, WI 53726, USA Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, 2500 Overlook Terrace, Madison, WI 53705, USA
Sanjay Asthana
Affiliation:
Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, J5/1 Mezzanine, 600 Highland Avenue, Madison, WI 53792, USA Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, 2500 Overlook Terrace, Madison, WI 53705, USA
Carey E. Gleason
Affiliation:
Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, J5/1 Mezzanine, 600 Highland Avenue, Madison, WI 53792, USA Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, 610 Walnut Street, 9th Floor, Madison, WI 53726, USA Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, 2500 Overlook Terrace, Madison, WI 53705, USA
*
*Correspondence and reprint requests to: Yue Ma, Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, J5/1 Mezzanine, 600 Highland Avenue, Madison, WI 53792, USA. E-mail: yma@medicine.wisc.edu
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Abstract

Objective:

This study investigated the latent factor structure of the NIH Toolbox Cognition Battery (NIHTB-CB) and its measurement invariance across clinical diagnosis and key demographic variables including sex, race/ethnicity, age, and education for a typical Alzheimer’s disease (AD) research sample.

Method:

The NIHTB-CB iPad English version, consisting of 7 tests, was administered to 411 participants aged 45–94 with clinical diagnosis of cognitively unimpaired, dementia, mild cognitive impairment (MCI), or impaired not MCI. The factor structure of the whole sample was first examined with exploratory factor analysis (EFA) and further refined using confirmatory factor analysis (CFA). Two groups were classified for each variable (diagnosis or demographic factors). The confirmed factor model was next tested for each group with CFA. If the factor structure was the same between the groups, measurement invariance was then tested using a hierarchical series of nested two-group CFA models.

Results:

A two-factor model capturing fluid cognition (executive function, processing speed, and memory) versus crystalized cognition (language) fit well for the whole sample and each group except for those with age < 65. This model generally had measurement invariance across sex, race/ethnicity, and education, and partial invariance across diagnosis. For individuals with age < 65, the language factor remained intact while the fluid cognition was separated into two factors: (1) executive function/processing speed and (2) memory.

Conclusions:

The findings mostly supported the utility of the battery in AD research, yet revealed challenges in measuring memory for AD participants and longitudinal change in fluid cognition.

Keywords

Exploratory factor analysisConfirmatory factor analysisMeasurement invarianceNIH ToolboxCognition batteryAlzheimer’s disease
Type
Regular Research
Information
Journal of the International Neuropsychological Society , Volume 27 , Issue 5 , May 2021 , pp. 412 - 425
Copyright
Copyright © INS. Published by Cambridge University Press, 2020

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