2000 journal article

Consequences of misspecifying assumptions in nonlinear mixed effects models

COMPUTATIONAL STATISTICS & DATA ANALYSIS, 34(2), 139–164.

By: A. Hartford* & M. Davidian*

author keywords: random effects; nonnormality; Laplace approximation; linearization
TL;DR: The consequences for population inferences using popular methods for fitting nonlinear mixed effects models when the normality assumption is inappropriate and/or the model is misspecified are investigated. (via Semantic Scholar)
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Added: August 6, 2018

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