Results 31 to 40 of about 6,102,677 (302)

ZERO-INFLATED NEGATIVE BINOMIAL REGRESSION FOR DIFFERENTIAL ABUNDANCE TESTING IN MICROBIOME STUDIES

Journal of Bioinformatics and Genomics, 2016
Motivation: The human microbiome plays an important role in human health and disease. The composition of the human microbiome is influenced by multiple factors and understanding these factors is critical to elucidate the role of the microbiome in health ...
Xinyan Zhang, Himel Mallick, Nengjun Yi
doaj   +1 more source

Count data regression modeling: an application to spontaneous abortion

Reproductive Health, 2020
Background In India, around 20,000 women die every year due to abortion-related complications. In count data modeling, there is sometimes a prevalence of zero counts.
Prashant Verma, Prafulla Kumar Swain, Kaushalendra Kumar Singh, Mukti Khetan   +3 more
doaj   +1 more source

Summary of results for the Negative Binomial Regression models.

, 2023
Summary of results for the Negative Binomial Regression models.
Jessica Andretta Mendes (15368901), Sophie O. Vanwambeke (8362926)   +1 more
core   +1 more source

Zero-inflated negative binomial regression.

, 2018
Zero-inflated negative binomial regression.
Nick Scott (837353), David P. Wilson (115579), Brett Sutton (5410199), Margaret E. Hellard (382375), Samuel W. Hainsworth (5410202), Paul M. Dietze (4057219)   +5 more
core   +1 more source

Negative binomial regression: POW effects on neighborhood crime.

, 2023
Negative binomial regression: POW effects on neighborhood crime.
James C. Wo (13245432)
core   +1 more source

Lognormal and Gamma Mixed Negative Binomial Regression

Proceedings of the ... International Conference on Machine Learning. International Conference on Machine Learning, 2012
In regression analysis of counts, a lack of simple and efficient algorithms for posterior computation has made Bayesian approaches appear unattractive and thus underdeveloped. We propose a lognormal and gamma mixed negative binomial (NB) regression model for counts, and present efficient closed-form Bayesian inference; unlike conventional Poisson ...
Zhou, M, Li, L, Dunson, D, Carin, L
openaire   +4 more sources

Application of negative binomial regression in analyzing factors that influence stunting in toddlers

Desimal
Stunting is a growth and development disorder caused by a lack of nutrition. This research aims to determine the significant factors that influence cases of stunting among toddlers in North Sumatra province in 2022. By using Negative Binomial Regression,
Allifiyani Tamimi, Ismail Husein
doaj   +1 more source

Re-sampling Techniques in Count Data Regression Models [PDF]

المجلة العراقية للعلوم الاحصائية, 2012
Modeling count variables is a common task in many application areas such as economics, social sciences, and medicine. The classical Poisson regression model for count data is often used and it is limited in these disciplines since count data sets ...
Zakariya Y. Algamal
doaj   +1 more source

Multivariate negative binomial regression results–neighbourhood perceptions.

, 2018
Multivariate negative binomial regression results–neighbourhood perceptions.
Alison Dias (6029660), Patricia Therese Campbell (5558441), Jodie McVernon (47926), Deborah Warr (3499097), Nicholas Geard (3135150)   +4 more
core   +1 more source

Incidence-rate ratios from negative binomial regression models predicting inflammation.

, 2023
Incidence-rate ratios from negative binomial regression models predicting inflammation.
Jennifer C. Cornman (17512285), Dana A. Glei (1939324), Maxine Weinstein (1939333), Jacob Witt (17512288)   +3 more
core   +1 more source