Odds ratios from logistic, geometric, Poisson, and negative binomial regression models [PDF]
BMC Medical Research Methodology, 2018 Background The odds ratio (OR) is used as an important metric of comparison of two or more groups in many biomedical applications when the data measure the presence or absence of an event or represent the frequency of its occurrence.
Christopher J. Sroka +1 more
doaj +3 more sources
Modeling microbial abundances and dysbiosis with beta-binomial regression [PDF]
Annals of Applied Statistics, 2020 Using a sample from a population to estimate the proportion of the population with a certain category label is a broadly important problem. In the context of microbiome studies, this problem arises when researchers wish to use a sample from a population ...
Bryan D Martin +2 more
exaly +4 more sources
Too many zeros and/or highly skewed? A tutorial on modelling health behaviour as count data with Poisson and negative binomial regression [PDF]
Health Psychology and Behavioral Medicine, 2021 Background Dependent variables in health psychology are often counts, for example, of a behaviour or number of engagements with an intervention. These counts can be very strongly skewed, and/or contain large numbers of zeros as well as extreme outliers ...
James A Green
exaly +3 more sources
Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression [PDF]
Genome Biology, 2019 Single-cell RNA-seq (scRNA-seq) data exhibits significant cell-to-cell variation due to technical factors, including the number of molecules detected in each cell, which can confound biological heterogeneity with technical effects.
Christoph Hafemeister, Rahul Satija
exaly +3 more sources
Human mobility and coronavirus disease 2019 (COVID-19): a negative binomial regression analysis [PDF]
Public Health, 2020 Lacin Idil Oztig, Oykum Esra Askin
exaly +3 more sources
Delta Boosting Implementation of Negative Binomial Regression in Actuarial Pricing
Risks, 2020 This study proposes an efficacious approach to analyze the over-dispersed insurance frequency data as it is imperative for the insurers to have decisive informative insights for precisely underwriting and pricing insurance products, retaining existing ...
Simon CK Lee
doaj +2 more sources
Estimation of safety performance functions for urban intersections using various functional forms of the negative binomial regression model and a generalized Poisson regression model [PDF]
Accident Analysis and Prevention, 2021 Muhammad Wisal Khattak +4 more
openalex +2 more sources
New two parameter hybrid estimator for zero inflated negative binomial regression models [PDF]
Scientific ReportsThe zero-inflated negative binomial regression (ZINBR) model is used for modeling count data that exhibit both overdispersion and zero-inflated counts. However, a persistent challenge in the efficient estimation of parameters within ZINBR models is the ...
Fatimah A. Almulhim +5 more
doaj +2 more sources
Beta-binomial regression and bimodal utilization. [PDF]
Health Serv Res, 2013 ObjectiveTo illustrate how the analysis of bimodal U‐shaped distributed utilization can be modeled with beta‐binomial regression, which is rarely used in health services research.Data Sources/Study SettingVeterans Affairs (VA) administrative data and Medicare claims in 2001–2004 for 11,123 Medicare‐eligible VA primary care users in 2000.Study DesignWe ...
Liu CF +3 more
europepmc +4 more sources
Marginal modeling in community randomized trials with rare events: Utilization of the negative binomial regression model. [PDF]
Clin Trials, 2022 Background/aims This work is motivated by the HEALing Communities Study, which is a post-test only cluster randomized trial in which communities are randomized to two different trial arms.
Westgate PM +5 more
europepmc +2 more sources