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 Kang KI, Kang K, Kim C.
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Zero inflated Poisson and negative binomial regression models: application in education.
Medical journal of the Islamic Republic of Iran, 2016 The number of failed courses and semesters in students are indicators of their performance. These amounts have zero inflated (ZI) distributions. Using ZI Poisson and negative binomial distributions we can model these count data to find the associated factors and estimate the parameters. This study aims at to investigate the important factors related to
Masoud, Salehi, Masoud, Roudbari
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Bayesian Zero Inflated Negative Binomial Regression Model for The Parkinson Data [PDF]
Proceedings of the Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bogor, Indonesia, 2020 Shafira Shafira +2 more
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A Commentary on Chatterjee Et Al. (2018): A Corrected Framework for Group Sparsity in Zero-Inflated Negative Binomial Models. [PDF]
Stat MedIqbal A, Mallick H, Ogundimu EO.
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The Impact of Extreme Weather on Dengue Fever in Guangzhou, China: A Zero-Inflated Negative Binomial Spatial Lag Analysis. [PDF]
GeohealthOuyang X, Shi F, Qiu Y, Deng G, Zhang S.
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New two parameter hybrid estimator for zero inflated negative binomial regression models. [PDF]
Sci RepAlmulhim FA +5 more
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Relationship between social network characteristics and falls among older adults living alone: an analysis using Zero-inflated negative binomial regression. [PDF]
BMC GeriatrShim MS, Park CG, Kim I.
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A Marginalized Zero-Inflated Negative Binomial Model for Spatial Data: Modeling COVID-19 Deaths in Georgia. [PDF]
Biom JMutiso F +5 more
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Association of body index with fecal microbiome in children cohorts with ethnic-geographic factor interaction: accurately using a Bayesian zero-inflated negative binomial regression model. [PDF]
mSystemsHuang J, Lu Y, Tian F, Ni Y.
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Statistical analysis of variability in TnSeq data across conditions using zero-inflated negative binomial regression. [PDF]
BMC Bioinformatics, 2019 Subramaniyam S +9 more
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