M
Michael O'Connell
Researcher at Becton Dickinson
Publications - 18
Citations - 1964
Michael O'Connell is an academic researcher from Becton Dickinson. The author has contributed to research in topics: Covariance & Cross-validation. The author has an hindex of 9, co-authored 18 publications receiving 1889 citations. Previous affiliations of Michael O'Connell include Research Triangle Park.
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Generalized linear mixed models a pseudo-likelihood approach
TL;DR: In this article, a pseudo-likelihood estimation procedure is developed to fit this class of mixed models based on an approximate marginal model for the mean response, implemented via iterated fitting of a weighted Gaussian linear mixed model to a modified dependent variable.
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A systematic approach to planning for a designed industrial experiment
David E. Coleman,Douglas C. Montgomery,Berton H. Gunter,Gerald J. Hahn,Perry D. Haaland,Michael O'Connell,Ramón V. León,Anne C. Shoemaker,Kwok-Leung Tsui +8 more
TL;DR: In this article, the authors present a set of tools for presenting generic technical issues and experimental features found in industrial experiments. And they also help experimenters discuss complex trade-offs between practical limitations and statistical preferences in the experiment.
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Calibration and assay development using the four-parameter logistic model
TL;DR: In this article, the four-parameter logistic model is used to estimate the response-error relationship (RER) and the variance function is estimated via generalized least squares/variance function estimation (GLS/VFE).
FUNFITS data analysis and statistical tools for estimating functions
TL;DR: A module of functions has been created to simplify and extend the fitting of curves and surfaces to data in FUNFITS, a programming language with some support from FORTRAN subroutines.
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A Nonparametric Regression Approach to Syringe Grading for Quality Improvement
TL;DR: An approach for extracting features from recordings based on nonparametric regression to build a classification model that incorporates the knowledge of the expert and is illustrated with the problem of grading of syringes from associated friction profile data.