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Maximum Likelihood Estimation of Non-Normal Random Effects and Random Errors in Nonlinear Random Effects Models

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Journal of Educational and Behavioral Statistics

Published online on

Abstract

Journal of Educational and Behavioral Statistics, Ahead of Print.
Nonlinear random effects models (NREMs) are particularly useful for modeling longitudinal data that follow intrinsically nonlinear trends. However, NREMs assume both random effects and random errors to be normally distributed, which is likely violated ...