Chapter 6. Designs for Multilevel Models

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

Published Online: 27 MAY 2009

DOI: 10.1002/9780470746912.ch6

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) Designs for Multilevel Models, in An Introduction to Optimal Designs for Social and Biomedical Research, John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9780470746912.ch6

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:

  • designs for multilevel models;
  • classical example hierarchically structured design - split-plot design;
  • statistical analysis of nested or hierarchically structured data - multilevel regression analysis;
  • cluster randomized trial;
  • selection bias, arising in cluster randomized trials;
  • maximum likelihood (ML) method;
  • randomization of a treatment - more efficient at the lowest level of a multilevel design

Summary

This chapter contains sections titled:

  • Design problem for multilevel models

  • The multilevel regression model

  • Cluster versus subject randomization

  • Cost function

  • Example: Nursing home study

  • Optimal design and power

  • Design effect in multilevel surveys

  • Matrix formulation of the multilevel model

  • Summary