Analyzing Longitudinal Data Using Natural Cubic Smoothing Splines

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


The analysis of longitudinal data has received widespread interest in the behavioral, educational, medical, and social sciences for many years. Many modeling techniques have been suggested for conducting such analyses, especially when the data exhibit complex nonlinear trajectory patterns. A major problem with many of these modeling techniques, however, is that they often either impose overly restrictive assumptions or can be computationally demanding. The purpose of this paper is to introduce a less known but highly effective modeling procedure that can be used to model complex nonlinear longitudinal data patterns. The procedure is illustrated using empirical data along with an easy to use computerized implementation.

Original languageEnglish (US)
Pages (from-to)965-971
Number of pages7
JournalStructural Equation Modeling
Issue number6
StatePublished - Nov 2 2018
Externally publishedYes


  • longitudinal data
  • natural cubic smoothing splines
  • nonlinear data

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