Automated selection of changepoints using empirical P-values and trimming.

ABSTRACT:

Objectives

One challenge that arises when analyzing mobile health (mHealth) data is that updates to the proprietary algorithms that process these data can change apparent patterns. Since the timings of these updates are not publicized, an analytic approach is necessary to determine whether changes in mHealth data are due to lifestyle behaviors or algorithmic updates. Existing methods for identifying changepoints do not consider multiple types of changepoints, may require prespecifying the number of changepoints, and often involve nonintuitive parameters. We propose a novel approach, Automated Selection of Changepoints using Empirical P-values and Trimming (ASCEPT), to select an optimal set of changepoints in mHealth data.

Materials and methods

ASCEPT involves 2 stages

SUBMITTER: Quinn M 

PROVIDER: S-EPMC9617685 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature