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AuthorWilliams, J. D.
AuthorBirch, J. B.
AuthorAbdel-Salam, A.-S. G.
Available date2015-11-05T10:33:07Z
Publication Date2015
Publication NameStatistics in Medicine
ResourceWiley Online library
CitationWilliams J. D., Birch J. B., and Abdel-Salam A.-S. G. (2015), Outlier robust nonlinear mixed model estimation, Statist. Med., 34, 1304–1316
ISSN1097-0258
URIhttp://dx.doi.org/10.1002/sim.6406
URIhttp://hdl.handle.net/10576/3720
AbstractIn 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®. Copyright © 2015 John Wiley & Sons, Ltd.
Languageen
PublisherJohn Wiley & Sons, Ltd.
Subjectdose-response
linearization
robust estimation
M-estimation
TitleOutlier robust nonlinear mixed model estimation
TypeArticle
Issue Number8
Volume Number34
dc.accessType Abstract Only


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