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Quantile dispersion graphs to compare the efficiencies of cluster randomized designs

  • S. Mukhopadhyay(corresponding author)
    ,
  • Stephen Warwick Looney
*Corresponding author for this work
Scholary Output:
Contribution to journal
Article
Peer-review

Open access

Abstract

The purpose of this article is to compare efficiencies of several cluster randomized designs using the method of quantile dispersion graphs (QDGs). A cluster randomized design is considered whenever subjects are randomized at a group level but analyzed at the individual level. A prior knowledge of the correlation existing between subjects within the same cluster is necessary to design these cluster randomized trials. Using the QDG approach, we are able to compare several cluster randomized designs without requiring any information on the intracluster correlation. For a given design, several quantiles of the power function, which are directly related to the effect size, are obtained for several effect sizes. The quantiles depend on the intracluster correlation present in the model. The dispersion of these quantiles over the space of the unknown intracluster correlation is determined, and then depicted by the QDGs. Two applications of the proposed methodology are presented.

Publication Information

Output type

Scholary Output:
Contribution to journal
Article
Peer-review

Original language

English (US)

Pages from-to (Number of pages)

Pages 1293-1305 (13 pages)

Journal (Volume, Issue Number)

Journal of Applied Statistics (Volume 36, Issue 11)

Publication milestones

  • Published - 11/01/2009

Publication status

Published - 11/01/2009

ISSN

0266-4763

Publication IDs

  • Scopus: 70350331505

Publication metrics

Metrics

SciVal
Author count
2
SciVal
citations
3
SciVal
Paper percentile
43
Fractional count
1
Fractional count
0.50
Fractional count
1
Fractional count
0.50
Fractional count
1
Fractional count
1
Scopus
citations

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5
Citation count
3