Chapter 7. Longitudinal Designs for Repeated Measurement Models

  1. Martijn P. F. Berger1 and
  2. Weng Kee Wong2

Published Online: 27 MAY 2009

DOI: 10.1002/9780470746912.ch7

An Introduction to Optimal Designs for Social and Biomedical Research

An Introduction to Optimal Designs for Social and Biomedical Research

How to Cite

Berger, M. P. F. and Wong, W. K. (2009) Longitudinal Designs for Repeated Measurement Models, in An Introduction to Optimal Designs for Social and Biomedical Research, John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9780470746912.ch7

Author Information

  1. 1

    Department of Methodology and Statistics, Maastricht University, The Netherlands

  2. 2

    Department of Biostatistics, School of Public Health, University of California, Los Angeles, USA

Publication History

  1. Published Online: 27 MAY 2009
  2. Published Print: 29 MAY 2009

ISBN Information

Print ISBN: 9780470694503

Online ISBN: 9780470746912

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Keywords:

  • longitudinal designs for repeated measurement models;
  • Abt et al. studying optimal designs for linear and quadratic growth curve models with auto-correlated errors;
  • repeated measurement design, having more compound symmetric structure;
  • counter-balanced design;
  • total body bone mineral density (TBBMD);
  • size of the auto-correlation parameter also influences the covariance pattern;
  • trade-off between random effects and correlation of errors, affecting optimality of a longitudinal design

Summary

This chapter contains sections titled:

  • Design problem for repeated measurements

  • The design

  • Analysis techniques for repeated measures

  • The linear mixed effects model for repeated measurement data

  • Variance–covariance structures

  • Estimation of parameters and efficiency

  • Bone mineral density example

  • Cost function

  • D-optimal designs for linear mixed effects models with auto-correlated errors

  • Miscellanea

  • Matrix formulation of the linear mixed effects model

  • Summary