Optimal Designs for Random Coefficient Regression Models with Heteroscedastic Errors

Abstract

The purpose of this article is to present the optimal designs based on D-, G-, A-, I-, and D β-optimality criteria for random coefficient regression (RCR) models with heteroscedastic errors. A sufficient condition for the heteroscedastic structure is given to make sure that the search of optimal designs can be confined at extreme settings of the design region when the criteria satisfy the assumption of the real valued monotone design criteria. Analytical solutions of D-, G-, A-, I-, and D β-optimal designs for the RCR models are derived. Two examples are presented for random slope models with specific heteroscedastic errors.