D-optimal population designs in linear mixed effects models for multiple longitudinal data

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 equivalen...

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Bibliographic Details
Published inStatistical theory and related fields Vol. 5; no. 2; pp. 88 - 94
Main Authors Jiang, Hongyan, Yue, Rongxian
Format Journal Article
LanguageEnglish
Published Taylor & Francis 03.04.2021
Taylor & Francis Group
Subjects
D-optimal designs
equivalence theorem
longitudinal data
multi-response linear mixed model
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Summary: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 the D-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.
ISSN:2475-4269
2475-4277
DOI:10.1080/24754269.2021.1884444