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A unifying framework for standard and covariate-adaptive randomization procedures based on minimizing suitable imbalance functions
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Journal of Biometrics & Biostatistics

ISSN: 2155-6180

Open Access

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


2nd International Conference and Exhibition on Biometrics & Biostatistics

June 10-12, 2013 Hilton Chicago/Northbrook, USA

Yuling Xiong

Posters: J Biomet Biostat

Abstract :

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.

Biography :

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.

Google scholar citation report
Citations: 2224

Journal of Biometrics & Biostatistics received 2224 citations as per google scholar report

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