Reach Us +44-1522-440391
Comparing Correlated Means In The Presence Of Incomplete Data Using A Permutation Test | 7610
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.

Comparing correlated means in the presence of incomplete data using a permutation test

2nd International Conference and Exhibition on Biometrics & Biostatistics

Desale Habtzghi

ScientificTracks Abstracts: J Biomet Biostat

DOI: 10.4172/2155-6180.S1.009

Analysis of incomplete pairs arises in both observational and experimental studies when some of the data are in the form of a paired sample and the rest of the data comprise two independent samples. We proposed a permutation based test. Our method uses the data from the two types of samples to test the difference between the mean responses. Our test statistic combines the observed mean difference for the complete pairs with the difference between the two means of the independent samples. We show by a simulation study that our statistic performs well in comparison to other methods. We apply our method to compare two methods for extracting DNA from coyote blood samples.

Desale Habtzghi has completed his Ph.D. in 2006 from the University of Georgia. Currently, he is working as an Assistant Professor in Department of Statistics at the University of Akron. His research interest is in Survival Analysis, Biostatistics, and Statistical Inferences (parametric and nonparametric).

Relevant Topics