Results 21 to 30 of about 3,153,646 (349)

Robust Negative Binomial Regression via the Kibria–Lukman Strategy: Methodology and Application [PDF]

Mathematics
Count regression models, particularly negative binomial regression (NBR), are widely used in various fields, including biometrics, ecology, and insurance.
Adewale F. Lukman, Olayan Albalawi, Mohammad Arashi, Jeza Allohibi, Abdulmajeed Atiah Alharbi, Rasha A. Farghali   +5 more
doaj   +2 more sources

Development of a personalized fall rate prediction model in community-dwelling older adults: a negative binomial regression modelling approach. [PDF]

BMC Geriatr, 2023
Wapp C, Biver E, Ferrari S, Zysset P, Zwahlen M.   +4 more
europepmc   +3 more sources

Binomial Regression Models with a Flexible Generalized Logit Link Function [PDF]

Symmetry, 2020
In binomial regression, a link function is used to join the linear predictor variables and the expectation of the response variable. This paper proposes a flexible link function from a new class of generalized logistic distribution, namely a flexible ...
Rindang Bangun Prasetyo, Heri Kuswanto, Nur Iriawan, Brodjol Sutijo Suprih Ulama   +3 more
openalex   +2 more sources

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

Count Data in Medical Research: Poisson Regression and Negative Binomial Regression

Anesthesia & Analgesia, 2021
Schober, Patrick, Vetter, Thomas R.
openaire   +5 more sources

Bayesian negative binomial regression for differential expression with confounding factors [PDF]

Bioinform., 2018
Siamak Zamani Dadaneh, Mingyuan Zhou, Xiaoning Qian   +2 more
openalex   +2 more sources

OVERDISPERSION HANDLING IN POISSON REGRESSION MODEL BY APPLYING NEGATIVE BINOMIAL REGRESSION

Barekeng, 2023
Statistical analysis that can be used if the response variable is quantified data is Poisson regression, assuming that the assumption must be met equidispersion, where the average response variable is the same as the standard deviation value.
Yesan Tiara, Muhammad Nur Aidi, Erfiani Erfiani, Rika Rachmawati   +3 more
doaj   +1 more source

Negative binomial regression [PDF]

Stata Technical Bulletin, 1994
Joseph Hilbe
core   +1 more source

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, Xiao G, Koh AY, Kim J, Li Q, Zhan X.   +5 more
europepmc   +3 more sources

Comparison of Chemical and Biological Wireworm Control Options in Serbian Sunflower Fields and a Proposition for a Refined Wireworm Damage Assessment

Agronomy, 2022
Recent European Union regulations aim at reducing the use of chemical pesticides in agriculture. In sunflower production in Serbia, the use of synthetic insecticides for soil and seed treatments has become a prevailing practice for wireworm (Coleoptera ...
Sonja Gvozdenac, Željko Milovac, Stefan Vidal, Zagorka Lozanov Crvenković, Ivana Štajner Papuga, Filip Franeta, Jelena Ovuka, Sandra Cvejić   +7 more
doaj   +1 more source