Multiple two-sample testing under arbitrary covariance dependency with an application in imaging mass spectrometry

DOI10.1002/bimj.202100328zbMATH Open1539.62332MaRDI QIDQ6550303

Thorsten Dickhaus, Vladimir Vutov

Publication date: 5 June 2024

Published in: Biometrical Journal (Search for Journal in Brave)

zbMATH Keywords

logistic regressionmultiple testingfalse discovery proportionsimultaneous statistical inferenceimaging mass spectrometrymatrix-assisted laser desorption/ionizationmultiple marginal models

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Multiplicity- and dependency-adjusted \(p\)-values for control of the family-wise error rate
• A general framework for multiple testing dependence
• A Factor Model Approach to Multiple Testing Under Dependence
• Estimating False Discovery Proportion Under Arbitrary Covariance Dependence
• Comment: FDP vs FDR and the Effect of Conditioning
• A Direct Approach to False Discovery Rates
• FarmTest: Factor-Adjusted Robust Multiple Testing With Approximate False Discovery Control
• Computing and approximating multivariate chi-square probabilities
• Correlated z-Values and the Accuracy of Large-Scale Statistical Estimates
• Correlation and Large-Scale Simultaneous Significance Testing
• Estimation of the False Discovery Proportion with Unknown Dependence
• Simultaneous Statistical Inference
• Large Covariance Estimation by Thresholding Principal Orthogonal Complements
• A versatile method for confirmatory evaluation of the effects of a covariate in multiple models

Related Items (1)

Multiple multi-sample testing under arbitrary covariance dependency

This page was built for publication: Multiple two-sample testing under arbitrary covariance dependency with an application in imaging mass spectrometry