Optimal designs for 2k factorial experiments with binary response
journal contributionposted on 21.06.2017 by J. Yang, A. Mandal, D. Majumdar
Any type of content formally published in an academic journal, usually following a peer-review process.
We consider the problem of obtaining D-optimal designs for factorial experiments with a binary response and k qualitative factors each at two levels. We obtain a characterization of locally D-optimal designs. We then develop efficient numerical techniques to search for locally D-optimal designs. Using prior distributions on the parameters, we investigate EW D-optimal designs that maximize the determinant of the expected information matrix. It turns out that these designs can be obtained easily using our algorithm for locally D-optimal designs and are good surrogates for Bayes D-optimal designs. We also investigate the properties of fractional factorial designs and study robustness with respect to the assumed parameter values of locally D-optimal designs.