Optimal designs for the emax, log-linear and exponential models
H. Dette,
C. Kiss,
M. Bevanda and
F. Bretz
Biometrika, 2010, vol. 97, issue 2, 513-518
Abstract:
We derive locally D- and ED p -optimal designs for the exponential, log-linear and three-parameter emax models. For each model the locally D- and ED p -optimal designs are supported at the same set of points, while the corresponding weights are different. This indicates that for a given model, D-optimal designs are efficient for estimating the smallest dose that achieves 100p% of the maximum effect in the observed dose range. Conversely, ED p -optimal designs also yield good D-efficiencies. We illustrate the results using several examples and demonstrate that locally D- and ED p -optimal designs for the emax, log-linear and exponential models are relatively robust with respect to misspecification of the model parameters. Copyright 2010, Oxford University Press.
Date: 2010
References: Add references at CitEc
Citations: View citations in EconPapers (5)
Downloads: (external link)
http://hdl.handle.net/10.1093/biomet/asq020 (application/pdf)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:oup:biomet:v:97:y:2010:i:2:p:513-518
Ordering information: This journal article can be ordered from
https://academic.oup.com/journals
Access Statistics for this article
Biometrika is currently edited by Paul Fearnhead
More articles in Biometrika from Biometrika Trust Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK.
Bibliographic data for series maintained by Oxford University Press ().