alexa Bayesian Adaptive Blinded Sample Size Adjustment For Comparing Two Normal Means
ISSN: 2167-065X

Clinical Pharmacology & Biopharmaceutics
Open Access

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)

Share This Page

Additional Info

Loading
Loading Please wait..
 

2nd International Summit on Clinical Pharmacy
December 02-03, 2014 DoubleTree by Hilton Hotel San Francisco Airport, USA

Andrew M Hartley
ScientificTracks Abstracts: Clinic Pharmacol Biopharm
DOI: 10.4172/2167-065X.S1.006
Abstract
Adaptive sample size adjustment (SSA) for clinical trials consists of examining early subsets of on-trial data, so as to adjust prior estimates of statistical parameters and sample size requirements. Blinded SSA, in particular, while in use already, seems poised to proliferate even further, due to recent draft guidance from the U.S. Food and Drug Administration. On the other hand, current blinded SSA methods offer little to no new information about the treatment effect (TE); the obvious resulting problem is that the TE estimate scientists might simply ?plug in? to the SS formulae could be severely wrong. This presentation describes a blinded SSA method which formally synthesizes sample data with prior knowledge about the TE and the variance. It evaluates the method in terms of the average absolute deviation from the targeted statistical power, the type 1 error rate, the bias of the estimated TE and other measures. Under the conditions considered, the method reduces that average absolute deviation by roughly 15% to 25%, relative to another, established method. Simulations show the method to induce minimal bias and negligible to no increase to the type 1 error rate.
Biography
Andrew Hartley, PhD, is an Associate Statistical Science Director in PPD?s Wilmington, North Carolina office and has over 8 years of experience as lead statistician and senior reviewer, on clinical trials in anti-infectives, oncology, neuroscience and metabolic disorders. He earned his PhD in Statistics at Old Dominion University in 1997, and has a total of 14 years of experience in clinical trials, with particular focus in longitudinal analysis, Bayesian inference, and decision analysis.
image PDF   |   image HTML
 

Relevant Topics

Peer Reviewed Journals
 
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2017-18
 
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

 
© 2008-2017 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version
adwords