ArticleThe annals of applied statistics2015
ASSESSING PHENOTYPIC CORRELATION THROUGH THE MULTIVARIATE PHYLOGENETIC LATENT LIABILITY MODEL.
Article in The annals of applied statistics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 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
19 citing papers in PubMed, 40 citations in OpenAlex.
- An Evolving View of Character Macroevolution.Systematic biology · 2026Review
- Practical Guide and Review of Fossil Tip-Dating in Phylogenetics.Systematic biology · 2026Review
- Quantum Speedups for Multiproposal MCMC.Bayesian analysis · 2025Article
- Diel activity correlates with colour pattern morphology of heterobranch sea slugs.The Journal of animal ecology · 2025Article
- Leveraging graphical model techniques to study evolution on phylogenetic networks.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025Review
- Fast Bayesian Inference of Phylogenies from Multiple Continuous Characters.Systematic biology · 2024Article
- Accelerating Bayesian inference of dependency between mixed-type biological traits.PLoS computational biology · 2023Article
- Data integration in Bayesian phylogenetics.Annual review of statistics and its application · 2023Article
- Principled, practical, flexible, fast: a new approach to phylogenetic factor analysis.Methods in ecology and evolution · 2022Article
- Statistical Challenges in Tracking the Evolution of SARS-CoV-2.Statistical science : a review journal of the Institute of Mathematical Statistics · 2022Article
- Mathematical models to study the biology of pathogens and the infectious diseases they cause.iScience · 2022Review
- From viral evolution to spatial contagion: a biologically modulated Hawkes model.Bioinformatics (Oxford, England) · 2022Article
- Inferring Phenotypic Trait Evolution on Large Trees With Many Incomplete Measurements.Journal of the American Statistical Association · 2022Article
- Relaxed Random Walks at Scale.Systematic biology · 2021Article
- Massive parallelization boosts big Bayesian multidimensional scaling.Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America · 2021Article
- On the Matrix Condition of Phylogenetic Tree.Evolutionary bioinformatics online · 2020Article
- Phylogenetic Factor Analysis.Systematic biology · 2018Article
- Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10.Virus evolution · 2018Article
- Emerging Concepts of Data Integration in Pathogen Phylodynamics.Systematic biology · 2017Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 5 institutions in 4 countries.
Funding
Abstract
Understanding which phenotypic traits are consistently correlated throughout evolution is a highly pertinent problem in modern evolutionary biology. Here, we propose a multivariate phylogenetic latent liability model for assessing the correlation between multiple types of data, while simultaneously controlling for their unknown shared evolutionary history informed through molecular sequences. The latent formulation enables us to consider in a single model combinations of continuous traits, discrete binary traits, and discrete traits with multiple ordered and unordered states. Previous approaches have entertained a single data type generally along a fixed history, precluding estimation of correlation between traits and ignoring uncertainty in the history. We implement our model in a Bayesian phylogenetic framework, and discuss inference techniques for hypothesis testing. Finally, we showcase the method through applications to columbine flower morphology, antibiotic resistance in
Indexed as
Identifiers
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.