Optimal designs for 2k factorial experiments with binary response J. Yang A. Mandal D. Majumdar 10027/21684 https://indigo.uic.edu/articles/journal_contribution/Optimal_designs_for_2k_factorial_experiments_with_binary_response/10772849 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. 2017-06-21 00:00:00 D-optimality EW D-optimal design fractional factorial design full factorial design generalized linear model uniform design