A Comparison of Event-Based Change-Point Models Using Novel Cognitive Domain Measures

Music City Center 

Change-point models are important tools in cognitive-aging research. Specifically, event-based change-point models enable differentiation in moderator effects on cognitive decline in relation to a pre-specified event. Here, we explore and compare methods for implementing event-based change-point models on novel harmonized cognitive measures from the National Alzheimer's Coordinating Center (NACC). The cognitive measures include three domains: memory, executive function, and language. We implement three methods using the R nlive package: a sigmoidal mixed model, a piecewise linear mixed model with abrupt change, and a piecewise linear mixed model with smooth polynomial transition. Each method is implemented for two cognitive events: mild cognitive impairment (MCI) diagnosis and Alzheimer's dementia (AD) diagnosis. We characterize each method's model fit and applied utility, especially when multiple moderators are included, to guide future modeling frameworks of the harmonized cognitive scores.

time-to-event

harmonized cognitive scores

change-point analysis

Alzheimer's dementia

mild cognitive impairment 

Biometrics Section