Early warning and predicting of COVID-19 using zero-inflated negative binomial regression model and negative binomial regression model [PDF]
BMC Infectious DiseasesBackground It is difficult to detect the outbreak of emergency infectious disease based on the exiting surveillance system. Here we investigate the utility of the Baidu Search Index, an indicator of how large of a keyword is in Baidu’s search volume, in ...
Wanwan Zhou +10 more
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Improved estimation in negative binomial regression. [PDF]
Stat Med, 2022 AbstractNegative binomial regression is commonly employed to analyze overdispersed count data. With small to moderate sample sizes, the maximum likelihood estimator of the dispersion parameter may be subject to a significant bias, that in turn affects inference on mean parameters.
Kenne Pagui EC, Salvan A, Sartori N.
europepmc +5 more sources
Driving Risk Assessment Using Near-Miss Events Based on Panel Poisson Regression and Panel Negative Binomial Regression [PDF]
Entropy, 2021 This study proposes a method for identifying and evaluating driving risk as a first step towards calculating premiums in the newly emerging context of usage-based insurance.
Shuai Sun +3 more
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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
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Statistical analysis of variability in TnSeq data across conditions using zero-inflated negative binomial regression [PDF]
BMC Bioinformatics, 2019 Background Deep sequencing of transposon mutant libraries (or TnSeq) is a powerful method for probing essentiality of genomic loci under different environmental conditions.
Siddharth Subramaniyam +8 more
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Bayesian negative binomial regression with spatially varying dispersion: Modeling COVID-19 incidence in Georgia. [PDF]
Spat Stat, 2022 Overdispersed count data arise commonly in disease mapping and infectious disease studies. Typically, the level of overdispersion is assumed to be constant over time and space. In some applications, however, this assumption is violated, and in such cases,
Mutiso F +5 more
europepmc +2 more sources
A Novel Phylogenetic Negative Binomial Regression Model for Count-Dependent Variables [PDF]
Biology, 2023 Regression models are extensively used to explore the relationship between a dependent variable and its covariates. These models work well when the dependent variable is categorical and the data are supposedly independent, as is the case with generalized
Dwueng-Chwuan Jhwueng, Chi-Yu Wu
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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
Too many zeros and/or highly skewed? A tutorial on modelling health behaviour as count data with Poisson and negative binomial regression. [PDF]
Health Psychol Behav Med, 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 ...
Green JA.
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Risk Factors Influencing Cyberbullying Perpetration among Middle School Students in Korea: Analysis Using the Zero-Inflated Negative Binomial Regression Model. [PDF]
Int J Environ Res Public Health, 2021 This cross-sectional descriptive study identified risk factors and predictors related to the perpetration of and potential for cyberbullying among adolescents, respectively. The analysis included a zero-inflated negative binomial regression model.
Kang KI, Kang K, Kim C.
europepmc +2 more sources