ArticleJournal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America2017
Regression Models For Multivariate Count Data.
Article in Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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
20 citing papers in PubMed.
- A New Dirichlet-Multinomial Mixture Regression Model for the Analysis of Microbiome Data.Statistics in medicine · 2025Article
- Analyzing microbiome data with taxonomic misclassification using a zero-inflated Dirichlet-multinomial model.BMC bioinformatics · 2025Article
- Single-cell gene regulatory network analysis for mixed cell populations.Quantitative biology (Beijing, China) · 2024Article
- Article
- Deciphering the 'gut-brain axis' through microbiome diversity.General psychiatry · 2023Review
- Statistical Picking of Multivariate Waveforms.Sensors (Basel, Switzerland) · 2022Article
- A semiparametric model for between-subject attributes: Applications to beta-diversity of microbiome data.Biometrics · 2022Article
- Analysis of injuries and deaths from road traffic accidents in Iran: bivariate regression approach.BMC emergency medicine · 2022Article
- Multivariate Analysis and Modelling of multiple Brain endOphenotypes: Let's MAMBO!Computational and structural biotechnology journal · 2021Review
- MicroBVS: Dirichlet-tree multinomial regression models with Bayesian variable selection - an R package.BMC bioinformatics · 2020Article
- A Searchable Database of Crystallization Cocktails in the PDB: Analyzing the Chemical Condition Space.Patterns (New York, N.Y.) · 2020Article
- New statistical method identifies cytokines that distinguish stool microbiomes.Scientific reports · 2019Article
- Zero-inflated generalized Dirichlet multinomial regression model for microbiome compositional data analysis.Biostatistics (Oxford, England) · 2019Article
- The molecular landscape of glioma in patients with Neurofibromatosis 1.Nature medicine · 2019Article
- The molecular landscape of glioma in patients with Neurofibromatosis 1.Nature medicine · 2019Article
- MGLM: An R Package for Multivariate Categorical Data Analysis.The R journal · 2018Article
- The molecular landscape of pediatric acute myeloid leukemia reveals recurrent structural alterations and age-specific mutational interactions.Nature medicine · 2018Article
- svt: Singular Value Thresholding in MATLAB.Journal of statistical software · 2017Article
- MDSINE: Microbial Dynamical Systems INference Engine for microbiome time-series analyses.Genome biology · 2016Article
- Multiple Comparisons With Overdispersed Multinomial Data: Methods, Properties and Application.Pharmaceutical statisticsArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Data with multivariate count responses frequently occur in modern applications. The commonly used multinomial-logit model is limiting due to its restrictive mean-variance structure. For instance, analyzing count data from the recent RNA-seq technology by the multinomial-logit model leads to serious errors in hypothesis testing. The ubiquity of over-dispersion and complicated correlation structures among multivariate counts calls for more flexible regression models. In this article, we study some generalized linear models that incorporate various correlation structures among the counts. Current literature lacks a treatment of these models, partly due to the fact that they do not belong to the natural exponential family. We study the estimation, testing, and variable selection for these models in a unifying framework. The regression models are compared on both synthetic and real RNA-seq data.
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.