False discovery rate control for lesion-symptom mapping with heterogeneous data via weighted \(p\)-values
From MaRDI portal
Publication:6649339
DOI10.1002/BIMJ.202300198MaRDI QIDQ6649339
Julius Fridriksson, Christopher Rorden, Joshua D. Habiger, Alexander C. McLain, Siyu Zheng
Publication date: 5 December 2024
Published in: Biometrical Journal (Search for Journal in Brave)
false discovery rateheterogeneous dataweighted \(p\)-valuesneuroimaging datavoxel-based lesion-symptom mapping
Cites Work
- Title not available (Why is that?)
- Title not available (Why is that?)
- Genome-wide significance levels and weighted hypothesis testing
- The positive false discovery rate: A Bayesian interpretation and the \(q\)-value
- A unified treatment of multiple testing with prior knowledge using the p-filter
- Power-enhanced multiple decision functions controlling family-wise error and false discovery rates
- Adaptive false discovery rate control under independence and dependence
- Simultaneous Testing of Grouped Hypotheses: Finding Needles in Multiple Haystacks
- Multiple Testing with the Structure-Adaptive Benjamini–Hochberg Algorithm
- False discovery control with p-value weighting
- Oracle and Adaptive Compound Decision Rules for False Discovery Rate Control
- Multiple Hypotheses Testing with Weights
- Weighted False Discovery Rate Control in Large-Scale Multiple Testing
- Adaptive False Discovery Rate Control for Heterogeneous Data
- Strong Control, Conservative Point Estimation and Simultaneous Conservative Consistency of False Discovery Rates: A Unified Approach
- A Direct Approach to False Discovery Rates
- Operating Characteristics and Extensions of the False Discovery Rate Procedure
- AdaPT: An Interactive Procedure for Multiple Testing with Side Information
- Optimal Control of False Discovery Criteria in the Two-Group Model
- Covariate Powered Cross-Weighted Multiple Testing
- The Optimal Discovery Procedure: A New Approach to Simultaneous Significance Testing
- False Discovery Rate Control With Groups
- Optimal Screening and Discovery of Sparse Signals with Applications to Multistage High Throughput Studies
- A Method to Increase the Power of Multiple Testing Procedures Through Sample Splitting
- Covariate Adaptive False Discovery Rate Control With Applications to Omics-Wide Multiple Testing
- LAWS: A Locally Adaptive Weighting and Screening Approach to Spatial Multiple Testing
- False Discovery Rate Control via Data Splitting
- New results for adaptive false discovery rate control with \(p\)-value weighting
This page was built for publication: False discovery rate control for lesion-symptom mapping with heterogeneous data via weighted \(p\)-values
Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6649339)