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Assisted Selection of Biomarkers by Linear Discriminant Analysis Effect Size LEfSe in Microbiome Data
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A depth-based global envelope test for comparing two groups of functions with applications to biomedical data.

Sara Lopez-Pintado1, Kun Qian2

  • 1Department of Health Sciences, Northeastern University, Boston, Massachusetts, USA.

Statistics in Medicine
|January 7, 2021
PubMed
Summary

This study introduces a novel depth-based global envelope test for comparing functional data groups. The method effectively identifies differences in growth patterns and brain scans, offering robust and visually informative results.

Keywords:
brain imagingdata depthenvelope testfunctional data

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Area of Science:

  • Statistics
  • Biomedical Data Analysis
  • Functional Data Analysis

Background:

  • Functional data analysis is crucial in emerging biomedical fields.
  • Traditional statistical methods have been extended for functional data.
  • Nonparametric and robust estimators enhance functional data analysis.

Purpose of the Study:

  • To develop depth-based global envelope tests for comparing two groups of functions or images.
  • To provide a method for ordering curves or images and defining robust order statistics.
  • To visualize specific portions of functional data contributing to hypothesis rejection.

Main Methods:

  • Development of depth-based global envelope tests.
  • Application of nonparametric and robust estimators.
  • Utilizing functional data depth for ordering and comparison.

Main Results:

  • The proposed envelope test provides global P-values and graphical displays.
  • Simulation studies show good empirical power and size, even with small differences.
  • The method is robust to outliers.

Conclusions:

  • The depth-based global envelope test is a powerful and robust tool for comparing functional data groups.
  • The methodology is applicable to diverse biomedical datasets, including growth patterns and brain imaging.
  • The test effectively visualizes group differences in functional data.