Earticle

초록

영어

The Mann-Whitney-Wilcoxon (MWW) test statistic, while distribution-free, suffers from a loss of efficacy for certain underlying distributions. In this manuscript, we instead use a data-adaptive weighted generalized Mann-Whitney-Wilcoxon (AWGMWW) test statistic, one that is optimal in the Pitman Asymptotic Efficacy (PAE) sense, to discern differences in hippocampus shape among twin populations with or without Major Depressive Disorder (MDD). Using this more powerful statistic, we verify, based on a previous study using the MWW statistic, that a high-risk group is more similar to the control group than the depressed group, the depressed group is more similar to the control group than the high-risk group, and the control group cannot be distinguished as more similar to one group or the other in terms of hippocampus shape.

목차

Abstract
 1. Introduction
  1.1. Nonparametric Statistics
  1.2. Major Depressive Disorder
  1.3. Computational Anatomy
  1.4. Goals
 2. Data
 3. Methods
  3.1. Image Processing
  3.2. Statistical Analysis
 4. Results
 5. Conclusions
 References

저자

• Nikhil Ram Mohan [ Johns Hopkins University, Center for Imaging Science ]
• Carey Priebe [ Johns Hopkins University, Center for Imaging Science ]
• Youngser Park [ Johns Hopkins University, Center for Imaging Science ]
• Majnu John [ Weill Cornell Medical College, Dept. of Biostatistics ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Bio-Science and Bio-Technology

• 간기

  격월간

• pISSN

  2233-7849

• 수록기간

  2009~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605