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Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
Published on: September 17, 2019
Analyzing developmental processes on an individual level using nonstationary time series modeling
Peter C M Molenaar1, Katerina O Sinclair, Michael J Rovine
1Department of Human Development and Family Studies, Pennsylvania State University, USA. pxm21@psu.edu
Abstract:
Individuals change over time, often in complex ways. Generally, studies of change over time have combined individuals into groups for analysis, which is inappropriate in most, if not all, studies of development. The authors explain how to identify appropriate levels of analysis (individual vs. group) and demonstrate how to estimate changes in developmental processes over time using a multivariate nonstationary time series model. They apply this model to describe the changing relationships between a biological son and father and a stepson and stepfather at the individual level. The authors also explain how to use an extended Kalman filter with iteration and smoothing estimator to capture how dynamics change over time. Finally, they suggest further applications of the multivariate nonstationary time series model and detail the next steps in the development of statistical models used to analyze individual-level data.
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