Measurement Models, Estimation, and the Study of Change

Kevin J. Grimm, Anthony P. Kuhl, Zhiyong Zhang

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


The study of change is based on the idea that the score or index at each measurement occasion has the same meaning and metric across time. In tests or scales with multiple items, such as those common in the social sciences, there are multiple ways to create such scores. Some options include using raw or sum scores (i.e., sum of item responses or linear transformation thereof), using Rasch-scaled scores provided by the test developers, fitting item response models to the observed item responses and estimating ability or aptitude, and jointly estimating the item response and growth models. We illustrate that this choice can have an impact on the substantive conclusions drawn from the change analysis using longitudinal data from the Applied Problems subtest of the Woodcock-Johnson Psycho-Educational Battery-Revised collected as part of the National Institute of Child Health and Human Development's Study of Early Child Care. Assumptions of the different measurement models, their benefits and limitations, and recommendations are discussed.

Original languageEnglish (US)
Pages (from-to)504-517
Number of pages14
JournalStructural Equation Modeling
Issue number3
StatePublished - Jul 2013
Externally publishedYes


  • change
  • growth
  • item response model
  • longitudinal
  • measurement

ASJC Scopus subject areas

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


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