A structural equation modeling approach for the analysis of cortisol data collected using pre-post-post designs

Michael Willoughby, Nathan Vandergrift, Clancy Blair, Douglas A. Granger

Research output: Contribution to journalArticlepeer-review

Abstract

This study introduces a novel application of structural equation modeling (SEM) for the analysis of cortisol data that are collected using a pre-post-post design. By way of an extended example, an SEM model is developed that permits an examination of both the overall level of cortisol, as well as changes in cortisol (reactivity and regulation), as predictors of cognitive (executive) and behavioral functioning in 3- to 5-year-old children (N= 171) attending Head Start. The SEM model makes use of the parameterization of latent curve models. Throughout the extended example, the strengths of using an SEM approach for the analysis of cortisol data that are collected using pre-post-post designs is highlighted.

Original languageEnglish (US)
Pages (from-to)125-145
Number of pages21
JournalStructural Equation Modeling
Volume14
Issue number1
DOIs
StatePublished - 2007

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Modeling and Simulation
  • Sociology and Political Science
  • Economics, Econometrics and Finance(all)

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