ODMIXED: A tool to obtain optimal designs for heterogeneous longitudinal studies with dropout

Shirley Ortega*, Frans E. S. Tan, Martijn P. F. Berger

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Web of Science)

Abstract

ODMIXED is a computer program to obtain optimal designs for linear mixed models of longitudinal studies. These designs account for heterogeneous correlated errors and for data with dropout. Designs are compared by using relative efficiencies, e.g., between a D-optimal design for homogeneous data and another for heterogeneous data or between a D-optimal design for complete data against another that optimizes designs when data is missing at random. Two examples are worked out to illustrate how researchers could use this computer program to profit of optimal design theory at the planning stage of longitudinal studies.
Original languageEnglish
Pages (from-to)62-71
JournalComputer Methods and Programs in Biomedicine
Volume101
Issue number1
DOIs
Publication statusPublished - Jan 2011

Keywords

  • D-optimal designs
  • Dropout
  • Heterogeneous autocorrelation
  • Linear mixed models
  • Longitudinal data
  • Relative efficiency

Cite this