Optimal designs for the prediction of individual parameters in hierarchical models

• 成果类型: Article
• 署名作者: Prus, Maryna; Schwabe, Rainer
• 署名单位: Otto von Guericke University
• 刊物名称: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
• ISSN/ISSBN: 1369-7412
• DOI: 10.1111/rssb.12105
• 发表日期: 2016
• 页码: 175-191
• 关键词: growth-curves; EQUIVALENCE

摘要

Characterizations of optimal designs are derived for the prediction of individual response curves within the framework of hierarchical linear mixed models. It is shown that the so-obtained optimal designs may differ substantially from those propagated in the literature so far and that the latter may become useless in terms of their performance.