Issues in Aggregating Time Series: Illustration Through an AR(1) Model

Intra-individual variation is time dependent variation within a single participant’s time series. When data are collected from more than one subject, methods developed for single subject intra-individual relationship may not fully work and laws governing inter-individual relationship may not apply to intra-individual relationship. There are relative few methods in dealing with the analysis of pooling multiple time series. This article aims to investigate empirically the comparability of methods for pooling time series data and to address related issues through an AR(1) model. In this article, multiple time series are formulated, pooling estimation methods are derived and compared, simulation studies results are summarized, and related practical issues are addressed.