Today, applying statistics in other sciences, including medical sciences, has become very common. Researchers consider optimal design as a tool to increase the efficiency of experiments. Pharmacokinetics is particularly important in the medical sciences as a branch of pharmacology that studies the performance of drugs in living organisms. This study aims to introduce optimal designs for models in pharmacokinetic studies. The models used in this paper are known as nonlinear models in the statistical literature. These models depend on specific parameters based on pharmacological factors and time as predictor variables. Optimal designs are obtained based on functions of the Fisher information matrix. These functions are known as optimal criteria. In this paper, we consider two criteria, A- and E-optimality. Based on these two criteria, locally optimal designs are obtained for the considered models.
Niaparest, M., Ahmadi, Z. & Heydari, A. (2022). A- and E-Optimal Designs for Statistical Models in
Pharmacokinetic Studies. Andishe_ye Amari, 27(1), 93-99.
MLA
Niaparest, M., Ahmadi, Z., & Heydari, A. "A- and E-Optimal Designs for Statistical Models in
Pharmacokinetic Studies", Andishe_ye Amari, 27, 1, 2022, 93-99.
HARVARD
Niaparest M., Ahmadi Z., Heydari A. (2022). 'A- and E-Optimal Designs for Statistical Models in
Pharmacokinetic Studies', Andishe_ye Amari, 27(1), pp. 93-99.
CHICAGO
M. Niaparest, Z. Ahmadi & A. Heydari, "A- and E-Optimal Designs for Statistical Models in
Pharmacokinetic Studies," Andishe_ye Amari, 27 1 (2022): 93-99,
VANCOUVER
Niaparest M., Ahmadi Z., Heydari A. A- and E-Optimal Designs for Statistical Models in
Pharmacokinetic Studies. Andishe_ye Amari. 2022;27(1):93-99 (In Persian).
