Nonlinear Growth Models as Measurement Models: A Second-Order Growth Curve Model for Measuring Potential

Daniel McNeish, Denis Dumas

Research output: Contribution to journalArticlepeer-review

25 Scopus citations


Recent methodological work has highlighted the promise of nonlinear growth models for addressing substantive questions in the behavioral sciences. In this article, we outline a second-order nonlinear growth model in order to measure a critical notion in development and education: potential. Here, potential is conceptualized as having three components—ability, capacity, and availability—where ability is the amount of skill a student is estimated to have at a given timepoint, capacity is the maximum amount of ability a student is predicted to be able to develop asymptotically, and availability is the difference between capacity and ability at any particular timepoint. We argue that single timepoint measures are typically insufficient for discerning information about potential, and we therefore describe a general framework that incorporates a growth model into the measurement model to capture these three components. Then, we provide an illustrative example using the public-use Early Childhood Longitudinal Study–Kindergarten data set using a Michaelis-Menten growth function (reparameterized from its common application in biochemistry) to demonstrate our proposed model as applied to measuring potential within an educational context. The advantage of this approach compared to currently utilized methods is discussed as are future directions and limitations.

Original languageEnglish (US)
Pages (from-to)61-85
Number of pages25
JournalMultivariate Behavioral Research
Issue number1
StatePublished - Jan 2 2017
Externally publishedYes


  • Non-linear growth
  • dynamic measurement model
  • second-order model

ASJC Scopus subject areas

  • Statistics and Probability
  • Experimental and Cognitive Psychology
  • Arts and Humanities (miscellaneous)


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