Residual Structures in Growth Models With Ordinal Outcomes

Kevin Grimm, Y. Liu

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


Growth models allow for the study of within-person change and between-person differences in within-person change. Typically, these models are applied to continuous variables where the residuals are assumed to be normally distributed. With normally distributed residuals there are a variety of residual structures that can be imposed and tested, which have been shown to affect model fit and parameter estimation. This article concerns residual structures in growth models with binary and ordered categorical outcomes using the probit link function. Different residual structures and their appropriateness for growth data are discussed and their use is illustrated with longitudinal data collected as part of Head Start’s Family and Child Experiences Survey 1997 Cohort. We close with recommendations for the specification and parameterization of growth models that use the probit link.

Original languageEnglish (US)
Pages (from-to)466-475
Number of pages10
JournalStructural Equation Modeling
Issue number3
StatePublished - May 3 2016


  • change
  • growth
  • ordinal

ASJC Scopus subject areas

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


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