alexa
Reach Us +44-1522-440391
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

Like us on:

OMICS International organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations
700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)
All submissions of the EM system will be redirected to Online Manuscript Submission System. Authors are requested to submit articles directly to Online Manuscript Submission System of respective journal.

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

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.
Relevant Topics
Top