sumSome-package: True Discovery Guarantee by Sum-Based Tests

In annavesely/sumSome: True Discovery Guarantee by Sum-Based Tests

True Discovery Guarantee by Sum-Based Tests

Description

It provides true discovery guarantees, using sum-based global statistics (sum of t-scores, p-value combinations, etc.). As main features, it produces permutation-based simultaneous lower confidence bounds for the proportion of active voxels in clusters for fMRI data, differentially expressed genes in pathways for gene expression data, and significant effects for multiverse analysis.

Author(s)

Anna Vesely and Xu Chen.

Maintainer: Anna Vesely <[e-mail]>

References

Goeman J. J. and Solari A. (2011). Multiple testing for exploratory research. Statistical Science, doi: 10.1214/1-STS356.

Tian J., Chen X., Katsevich E., Goeman J. J. and Ramdas A. (2022). Large-scale simultaneous inference under dependence. Scandinavian Journal of Statistics, doi: 10.1111/sjos.12614.

Vesely A., Finos L., and Goeman J. J. (2023). Permutation-based true discovery guarantee by sum tests. Journal of the Royal Statistical Society, Series B (Statistical Methodology), doi: 10.1093/jrsssb/qkad019.

See Also

fMRI cluster analysis: brainScores, brainPvals, brainClusters, brainAnalysis

Gene expression pathway analysis: geneScores, genePvals, geneAnalysis

Multiverse analysis: pimaAnalysis

General setting: sumStats and sumPvals (permutations), sumStatsPar and sumPvalsPar (parametric)

annavesely/sumSome documentation built on Jan. 28, 2025, 8:15 a.m.