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Updated: Apr 18, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
Published on: July 3, 2020
Outlier robust nonlinear mixed model estimation
James D Williams1, Jeffrey B Birch, Abdel-Salam G Abdel-Salam
1Business Analytics, Dow AgroSciences, 9330 Zionsville Rd., Indianapolis, IN, 46268, U.S.A.
Abstract:
In standard analyses of data well-modeled by a nonlinear mixed model, an aberrant observation, either within a cluster, or an entire cluster itself, can greatly distort parameter estimates and subsequent standard errors. Consequently, inferences about the parameters are misleading. This paper proposes an outlier robust method based on linearization to estimate fixed effects parameters and variance components in the nonlinear mixed model. An example is given using the four-parameter logistic model and bioassay data, comparing the robust parameter estimates with the nonrobust estimates given by SAS(®).
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