Friday, February 9 2018, 3:30pm Brooks Hall Room 434 We discuss optimal designs for the panel mixed logit model. The panel mixed logit model is usually used for the analysis of discrete choice experiments. The information matrix used in design criteria does not have a closed form expression and it is computationally difficult to evaluate the information matrix numerically. We derive the information matrix and use the obtained form to propose three methods to approximate the information matrix. The approximations are compared to the information matrix in simulations to see whether the design criteria based on them can yield similar orderings of designs as the criteria based on the information matrix. We also propose three alternatives to the information matrix based on approximate analysis methods for the generalized linear mixed models given the panel mixed logit model is a special case of the generalized linear mixed models. The alternatives are used in computer search to find optimal designs and compared based on the efficiencies of the best designs and time needed to find those designs.
