The main purpose of this paper is to investigate D-optimal population designs in multi-response linear mixed models for longitudinal data.Observations of each response variable within subjects are assumed to have a fi...The main purpose of this paper is to investigate D-optimal population designs in multi-response linear mixed models for longitudinal data.Observations of each response variable within subjects are assumed to have a first-order autoregressive structure,possibly with observation error.The equivalence theorems are provided to characterise theD-optimal population designs for the estimation of fixed effects in the model.The semi-Bayesian D-optimal design which is robust against the serial correlation coefficient is also considered.Simulation studies show that the correlation between multi-response variables has tiny effects on the optimal design,while the experimental costs are important factors in the optimal designs.展开更多
基金partly supported by the National Natural Science Foundation of China(Nos.11971318,11871143)Shanghai Rising-Star Program(No.20QA1407500).
文摘The main purpose of this paper is to investigate D-optimal population designs in multi-response linear mixed models for longitudinal data.Observations of each response variable within subjects are assumed to have a first-order autoregressive structure,possibly with observation error.The equivalence theorems are provided to characterise theD-optimal population designs for the estimation of fixed effects in the model.The semi-Bayesian D-optimal design which is robust against the serial correlation coefficient is also considered.Simulation studies show that the correlation between multi-response variables has tiny effects on the optimal design,while the experimental costs are important factors in the optimal designs.
