Activity Number:
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337
- Interim Monitoring and Analyses: Two-Stage, Multi-Stage, and Group Sequential Designs
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Type:
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Contributed
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Date/Time:
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Tuesday, August 1, 2017 : 10:30 AM to 12:20 PM
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Sponsor:
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Biopharmaceutical Section
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Abstract #322636
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View Presentation
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Title:
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Extension of the Two-Stage Randomized Trial Design for Testing Treatment, Self-Selection, and Treatment Preference Effects to Binary Outcomes
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Author(s):
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Briana Cameron* and Denise Esserman and Peter Peduzzi
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Companies:
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Yale University and Yale School of Public Health and Yale School of Public Health
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Keywords:
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two-stage ;
preference ;
sample size ;
binomial
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Abstract:
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While traditional clinical trials seek to determine treatment efficacy within a specified population, they often ignore the role of a patient's treatment preference on his or her treatment response. The two-stage (doubly) randomized preference trial design provides one approach for researchers seeking to disentangle preference effects from treatment effects. Currently, this two-stage design is limited to the design and analysis of continuous outcome variables; in this presentation, we extend this current design to include binary variables. First, we present the test statistics for testing the preference, selection and treatment effects in a two-stage randomized design with a binary outcome measure, with and without stratification. We also derive closed-form sample size formulae to indicate the number of patients needed to detect each effect. A series of simulation studies were done to explore the properties and efficiency of both the un-stratified and stratified doubly randomized trial designs. Finally, we demonstrate the applicability of these methods using an example of a trial of Hepatitis C treatment.
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Authors who are presenting talks have a * after their name.
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