Abstract

In observational studies, we evaluate participants at multiple time points to describe their longitudinal change pattern. The exact schedules of those evaluations (i.e., dates of participants' visits) are often pre-determined to accommodate ease of project management and compliance. For example, scheduling those evaluations at equally spaced time intervals is common. However, recent publications based on simulated experiments indicate that given a model format, the power of studies and the precision of model parameter estimators relates to the participants' visiting scheme. Therefore, in this paper, we investigate how to schedule participants' visits in order to better study the accelerated cognitive decline of senior adults, where a broken-stick model is often applied.
We formulate this optimal design problem on scheduling participants' visiting into a high-dimensional optimization problem and derive its approximate solution by adding reasonable constraints. Based on this approximation, we propose a novel design of the visiting scheme that aims to maximize the power (i.e. reduce the variance of estimators) in identifying the onset of accelerated decline. Using simulation studies and evidence from real data, we demonstrate that our design outperforms the standard equally-spaced one when we have strong prior knowledge of the change points.
This novel design help researchers plan their longitudinal studies with improved power in detecting pattern change without collecting extra data. Also, this individual-level scheduling system helps monitor seniors' cognitive function and, therefore, benefits the development of personal-level treatment for cognitive decline, which agrees with the trend of the health care system.