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