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Updated: Jul 5, 2025

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
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Identifiability and estimability of Bayesian linear and nonlinear crossed random effects models.

Corissa T Rohloff1, Nidhi Kohli1, Eric F Lock2

  • 1Quantitative Methods in Education, Department of Educational Psychology, University of Minnesota, Minneapolis, Minnesota, USA.

The British Journal of Mathematical and Statistical Psychology
|January 24, 2024
PubMed
Summary

This study introduces a Bayesian piecewise crossed random effects model (CREM) for nonlinear growth. Sufficient repeated measurements are crucial for accurately estimating group effects in longitudinal data analysis.

Keywords:
Bayesian inferencecrossed random effectsmodel identificationpiecewise functionrandom effects models

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