This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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360
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Type:
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Contributed
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Date/Time:
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Tuesday, August 3, 2010 : 10:30 AM to 12:20 PM
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Sponsor:
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Biometrics Section
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Abstract - #306870 |
Title:
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Improving Small-Sample Inference in Group-Randomized Trials with Binary Outcomes
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Author(s):
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Philip Westgate*+ and Thomas Braun
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Companies:
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University of Michigan and University of Michigan
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Address:
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648 Manor Dr., Ann Arbor, MI, 48105,
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Keywords:
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Group Randomized Trials ;
Binary Outcomes ;
Quasi-Likelihood ;
Wald Statistic
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Abstract:
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Group Randomized Trials typically randomize a small number of clusters composed of a large number of subjects, resulting in over-dispersion quantified using the intra-cluster correlation coefficient (ICC). When subject-level outcomes are binary, modeling can be done using quasi-likelihood with a logistic link. In this setting, the Wald statistic used to test for a treatment effect, which asymptotically has a standard normal distribution, may have a variance less than one, resulting in a test size smaller than its nominal value. When the ICC is known, we develop a method for adjusting the estimated standard error such that the Wald statistic approximately has a standard normal distribution. We also propose a way to resolve non-nominal test sizes when the ICC is estimated. Through simulation results covering a variety of realistic settings, we examine the performance of our methods.
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