Analyzing Developmental Processes on an Individual Level Using Nonstationary Time Series Modeling

Peter C.M. Molenaar, Katerina O. Sinclair, Michael J. Rovine, Nilam Ram, Sherry E. Corneal

Research output: Contribution to journalArticlepeer-review

100 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)260-271
Number of pages12
JournalDevelopmental psychology
Issue number1
StatePublished - Jan 2009

All Science Journal Classification (ASJC) codes

  • Demography
  • Developmental and Educational Psychology
  • Life-span and Life-course Studies


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