Design considerations for small experiments and simple logistic regression

DOI10.1080/00949650701609006zbMath1161.62039OpenAlexW2170908478MaRDI QIDQ3615057

Kenneth Graham Russell, J. A. Eccleston, David C. Woods, Susan M. Lewis

Publication date: 17 March 2009

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949650701609006

zbMATH Keywords

optimalitybiasintegrated mean square errormaximum penalized likelihoodgeneralized linear models

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Optimal statistical designs (62K05) Generalized linear models (logistic models) (62J12)

Related Items (2)

Modified D-optimal design for logistic model ⋮ The effect of small sample on optimal designs for logistic regression models

Cites Work

• Model-oriented design of experiments
• Designs in nonlinear regression by stochastic minimization of functionals of the mean square error matrix
• Computing Distributions for Exact Logistic Regression
• Experimental Design for Binary Data
• Small-sample techniques for comparing several logistic regression slopes to a standard
• Bias reduction of maximum likelihood estimates
• A Basis for the Selection of a Response Surface Design
• Optimal designs for binary data under logistic regression
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