Robust estimation of general linear mixed effects models
METADATA ONLY
Loading...
Author / Producer
Date
2023
Publication Type
Book Chapter
ETH Bibliography
yes
Citations
Altmetric
METADATA ONLY
Data
Rights / License
Abstract
The classical REML estimator for fitting a general linear mixed effects model is modified by bounding the terms appearing in the scoring equations. This leads to a generally applicable robust M-type estimator that we call robust scoring equations estimator. It requires only minor assumptions on the covariance matrices (block diagonal for the random effects and diagonal, known up to scale for the residual errors) additional to those of the classical methods. The structure of the data is arbitrary as long as the model is estimable in the classical sense. The estimator can detect and contain the effect of outliers in moderately contaminated datasets. Contamination is detected and treated at all levels of variability of the model, e.g., at both the subject and the observation level for a one-way ANOVA model. The estimator's properties are studied by simulation and two examples. One example implies crossed random effects, for which the known robust methods are not applicable.
Permanent link
Publication status
published
Book title
Robust and Multivariate Statistical Methods: Festschrift in Honor of David E. Tyler
Journal / series
Volume
Pages / Article No.
297 - 322
Publisher
Springer