ArticleStatistics surveys2016
Measuring multivariate association and beyond.
Article in Statistics surveys, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed.
- Vaginal microbiota impacts of a Lactobacillus crispatus live biotherapeutic and predictors of colonization in randomized controlled trial.Cell host & microbe · 2026Trial
- Statistical Methods for Detecting Nonlinear Relationships in Gene Expression and Omics Data: A Review.International journal of molecular sciences · 2026Review
- How quantum-chemical geometry optimization level affects classical 3D descriptors and QSAR performance: a comparative study.Journal of cheminformatics · 2026Article
- Heart rate variability, ECG minor changes, and HRV-ECG coupling associated with an adjunctive structured breathing-meditation protocol in combat-exposed military personnel.Frontiers in network physiology · 2026Article
- A powerful framework for differential co-expression analysis of general risk factors.Bioinformatics (Oxford, England) · 2025Article
- Microbiota effects and predictors ofmedRxiv : the preprint server for health sciences · 2025Article
- Craniofacial integration and modularity in untreated cleft lip and palate.Clinical oral investigations · 2025Article
- Identifying latent genetic interactions in genome-wide association studies using multiple traits.Genome medicine · 2024Article
- Diagnostic checks in time series models based on a new correlation coefficient of residuals.Journal of applied statistics · 2024Article
- An exploration of linkage fine-mapping on sequences from case-control studies.Genetic epidemiology · 2023Article
- Delving into gene-set multiplex networks facilitated by a k-nearest neighbor-based measure of similarity.Computational and structural biotechnology journal · 2023Article
- Detecting the Guttman effect with the help of ordinal correspondence analysis in synchrotron X-ray diffraction data analysis.Journal of applied statistics · 2022Article
- Comparative analysis of molecular fingerprints in prediction of drug combination effects.Briefings in bioinformatics · 2021Article
- The interaction of resource use and gene flow on the phenotypic divergence of benthic and pelagic morphs of Icelandic Arctic charr (Ecology and evolution · 2021Article
- Microbial biogeography and ecology of the mouth and implications for periodontal diseases.Periodontology 2000 · 2020Review
- Divergent Allometric Trajectories in Gene Expression and Coexpression Produce Species Differences in Sympatrically Speciating Midas Cichlid Fish.Genome biology and evolution · 2019Article
- The Contribution Plot: Decomposition and Graphical Display of the RV Coefficient, with Application to Genetic and Brain Imaging Biomarkers of Alzheimer's Disease.Human heredity · 2019Article
- KERNEL-PENALIZED REGRESSION FOR ANALYSIS OF MICROBIOME DATA.The annals of applied statistics · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Simple correlation coefficients between two variables have been generalized to measure association between two matrices in many ways. Coefficients such as the RV coefficient, the distance covariance (dCov) coefficient and kernel based coefficients are being used by different research communities. Scientists use these coefficients to test whether two random vectors are linked. Once it has been ascertained that there is such association through testing, then a next step, often ignored, is to explore and uncover the association's underlying patterns. This article provides a survey of various measures of dependence between random vectors and tests of independence and emphasizes the connections and differences between the various approaches. After providing definitions of the coefficients and associated tests, we present the recent improvements that enhance their statistical properties and ease of interpretation. We summarize multi-table approaches and provide scenarii where the indices can provide useful summaries of heterogeneous multi-block data. We illustrate these different strategies on several examples of real data and suggest directions for future research.
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.