Modelling the decline pattern in functional measures from a prevalent cohort study

In studying decline among cognitively impaired people, a prevalent cohort study design is commonly used to account for entry into the study at different levels of impairment. The data set typically consists of many short series of repeated measurements collected over time. However, the time origin, such as time of disease/impairment onset, is often uncertain. In order to model non-linear decline patterns in functional test scores and associated risk factors with such data, we propose two approaches as alternatives to Liu et al. One approach models change over adjacent visits with varying time intervals. The second models the change since baseline using a random effect for heterogeneity of change. We used these two approaches to examine the decline in cognitive test scores among special care unit (SCU) and non-SCU residents at the New York sites of the National Institute on Aging (NIA) collaborative studies of special dementia care. The analyses suggest that, controlling for several covariates, SCU residents experienced more rapid cognitive decline than did non-SCU residents. The relative advantages and disadvantages of the two models are discussed.