Hybrid Logistic and Confined Exponential Growth Models: Estimation using SEM Software

Phillip K Wood

No xv84q, OSF Preprints from Center for Open Science

Abstract: The logistic and confined exponential curves are frequently used in studies of growth and learning. These models, which are nonlinear in their parameters, can be estimated using structural equation modeling software. This paper proposes a single hybrid model which is a weighted combination of both models. Example Mplus code for the model is provided. In order to assess whether the model can be successfully fit using SEM software and is preferable to either individual model, Monte Carlo simulations varying the number of measurement occasions (5, 10, and 15), internal consistency (α = .5, .7, and .8), and sample size (N = 1,000, 500, and 300) were examined. Convergence failures were appreciable when model parameters were equal to special cases of logistic or confined exponential curves. At least ten measurement occasions and a moderate degree of reliability ( >0.7) were required to identify the model as superior to its stand-alone alternatives. Keywords: Growth; Structural Equation Modeling; Logistic Curve; Confined Exponential Curve

Date: 2023-02-08
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Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:xv84q

DOI: 10.31219/osf.io/xv84q

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