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Wiley InterScience

Biometrics

Biometrics

Volume 63 Issue 3, Pages 699 - 707

Published Online: 13 Mar 2007

©2009 International Biometric Society



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Sample Size Determination for Hierarchical Longitudinal Designs with Differential Attrition Rates
Anindya Roy 1,2 , Dulal K. Bhaumik 1,3,4 , Subhash Aryal 1,3,4 , and Robert D. Gibbons 1,3,4 ,
  1 Center for Health Statistics, University of Illinois at Chicago, 1601 W. Taylor St., Chicago, Illinois 60612, U.S.A.   2 Department of Mathematics and Statistics, University of Maryland, Baltimore County, Baltimore, Maryland 21250, U.S.A.   3 Department of Psychiatry, University of Illinois at Chicago, 1601 W. Taylor St., Chicago, Illinois 60612, U.S.A.   4 Division of Epidemiology and Biostatistics, University of Illinois at Chicago, 1601 W. Taylor St. Chicago, Illinois 60612, U.S.A.
Correspondence to   * email: rdgib@uic.edu
Copyright 2007, The International Biometric Society
KEYWORDS
Cost analysis • Dropouts • Mixed effects • Power analysis • Profile analysis • Three-level nested design

ABSTRACT

Summary .   We consider the problem of sample size determination for three-level mixed-effects linear regression models for the analysis of clustered longitudinal data. Three-level designs are used in many areas, but in particular, multicenter randomized longitudinal clinical trials in medical or health-related research. In this case, level 1 represents measurement occasion, level 2 represents subject, and level 3 represents center. The model we consider involves random effects of the time trends at both the subject level and the center level. In the most common case, we have two random effects (constant and a single trend), at both subject and center levels. The approach presented here is general with respect to sampling proportions, number of groups, and attrition rates over time. In addition, we also develop a cost model, as an aid in selecting the most parsimonious of several possible competing models (i.e., different combinations of centers, subjects within centers, and measurement occasions). We derive sample size requirements (i.e., power characteristics) for a test of treatment-by-time interaction(s) for designs based on either subject-level or cluster-level randomization. The general methodology is illustrated using two characteristic examples.


Received May 2006. Revised September 2006. Accepted November 2006.

DIGITAL OBJECT IDENTIFIER (DOI)
10.1111/j.1541-0420.2007.00769.x About DOI

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