Optimal design for experiments with possibly incomplete observations

Lee, Kim May and Biedermann, Stefanie and Mitra, Robin (2017) Optimal design for experiments with possibly incomplete observations. Statistica Sinica. ISSN 1017-0405

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Abstract

Missing responses occur in many industrial or medical experiments, for example in clinical trials where slow acting treatments are assessed. Finding efficient designs for such experiments can be problematic since it is not known at the design stage which observations will be missing. The design literature mainly focuses on assessing robustness of designs for missing data scenarios, rather than finding designs which are optimal in this situation. Imhof, Song and Wong (2002) propose a framework for design search, based on the expected information matrix. We develop a new approach which includes Imhof, Song and Wong (2002)'s method as special case and justifies its use retrospectively. Our method is illustrated through a simulation study based on real data from an Alzheimer's disease trial.

Item Type:
Journal Article
Journal or Publication Title:
Statistica Sinica
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1800/1804
Subjects:
ID Code:
123894
Deposited By:
Deposited On:
08 Mar 2018 10:26
Refereed?:
Yes
Published?:
Published
Last Modified:
18 Sep 2020 04:03