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A Unifying Framework For Standard And Covariate-adaptive Randomization Procedures Based On Minimizing Suitable Imbalance Functions | 7691
ISSN: 2155-6180

Journal of Biometrics & Biostatistics
Open Access

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A unifying framework for standard and covariate-adaptive randomization procedures based on minimizing suitable imbalance functions

2nd International Conference and Exhibition on Biometrics & Biostatistics

Yuling Xiong

Posters: J Biomet Biostat

DOI: 10.4172/2155-6180.S1.018

Minimization is based on minimizing an imbalance function defined in terms of one or more covariates. Standard (non- adaptive) randomization procedures, on the other hand, generally do not specify or try to minimize an imbalance function. However, it turns out that they may be formulated in this manner. Doing so places adaptive and standard randomization procedures within the same framework, and also suggests novel randomization procedures that combine the best elements of both.
Yuling xiong is a second year Master student from Loyola University Chicago, Department of Applied Statistics. She finished her Bachelor's degree in Applied Mathematics in China. Her research focus on game theory, right censored survival data and GWAS data analysis.
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