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

Abstract

AbstractObjective: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.