Yao Shi, Arizona State University

• Title: Optimal designs under logistic mixed model

• Abstract: While generalized linear mixed models are useful, optimal design questions for such models are challenging due to complexity of the information matrices. For longitudinal data, after considering three approximations of the information matrices, we propose an approximation based on the penalized quasi-likelihood method. As an illustration, optimal designs are derived for a study on self-reported disability in older women. We also study the robustness of these optimal designs to misspecification of the covariance matrix for rondom effects.