| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1148505 | Journal of Statistical Planning and Inference | 2014 | 6 Pages |
•Robust designs against missing data for two-level orthogonal main-effect plans are investigated.•Theoretical results regarding the nearly saturated designs are developed.•A catalogue of the maximally robust designs with practical run-sizes is provided.
A new class of robust designs against missing data, called the minimum breakdown designs, is proposed for two-level orthogonal main-effect plans. The minimum breakdown designs provide the highest probability to derive a non-singular residual design for estimating the grand mean and all the main effects, when a fraction of experimental data is unavailable. Some theoretical and computational results for characterizing the minimum breakdown designs are developed. In addition, a catalogue of the proposed designs with practical run-sizes is presented for multifactorial experiments.
