Factors related to baseline CD4 cell counts in HIV/AIDS patients: comparison of poisson, generalized poisson and negative binomial regression models. [PDF]
BMC Res Notes, 2021 Objective CD4 Lymphocyte Count (CD4) is a major predictor of HIV progression to AIDS. Exploring the factors affecting CD4 levels may assist healthcare staff and patients in management and monitoring of health cares.
Farhadian M +3 more
europepmc +2 more sources
Human mobility and coronavirus disease 2019 (COVID-19): a negative binomial regression analysis. [PDF]
Public Health, 2020 Objectives This study aimed to examine the link between human mobility and the number of coronavirus disease 2019 (COVID-19)–infected people in countries. Study design Our data set covers 144 countries for which complete data are available.
Oztig LI, Askin OE.
europepmc +2 more sources
Disease Mapping via Negative Binomial Regression M-quantiles [PDF]
Statistics in Medicine, 2013 We introduce a semi-parametric approach to ecological regression for disease mapping, based on modelling the regression M-quantiles of a Negative Binomial variable. The proposed method is robust to outliers in the model covariates, including those due to
Chambers, Ray +2 more
core +5 more sources
Double Generalized Beta-Binomial and Negative Binomial Regression Models
Revista Colombiana de Estadística, 2017 Overdispersion is a common phenomenon in count datasets, that can greatly affect inferences about the model. In this paper develop three joint mean and dispersion regression models in order to fit overdispersed data.
EDILBERTO CEPEDA-CUERVO +1 more
doaj +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
A Bayesian zero-inflated negative binomial regression model for the integrative analysis of microbiome data. [PDF]
Biostatistics, 2021 Microbiome omics approaches can reveal intriguing relationships between the human microbiome and certain disease states. Along with identification of specific bacteria taxa associated with diseases, recent scientific advancements provide mounting ...
Jiang S +5 more
europepmc +3 more sources
NIMBus: a negative binomial regression based Integrative Method for mutation Burden Analysis [PDF]
BMC Bioinformatics, 2020 Background Identifying frequently mutated regions is a key approach to discover DNA elements influencing cancer progression. However, it is challenging to identify these burdened regions due to mutation rate heterogeneity across the genome and across ...
Jing Zhang +6 more
doaj +2 more sources
Bayesian Zero-Inflated Negative Binomial Regression Based on Pólya-Gamma Mixtures. [PDF]
Bayesian Anal, 2019 Motivated by a study examining spatiotemporal patterns in inpatient hospitalizations, we propose an efficient Bayesian approach for fitting zero-inflated negative binomial models.
Neelon B.
europepmc +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
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 +2 more sources