Results 31 to 40 of about 540,910 (340)

Risk Factors Influencing Cyberbullying Perpetration among Middle School Students in Korea: Analysis Using the Zero-Inflated Negative Binomial Regression Model. [PDF]

open access: yesInt 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

Factors related to baseline CD4 cell counts in HIV/AIDS patients: comparison of poisson, generalized poisson and negative binomial regression models. [PDF]

open access: yesBMC 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

Negative binomial regression [PDF]

open access: yesStata Technical Bulletin, 1994
Joseph Hilbe
core   +1 more source

POISSON REGRESSION MODELS TO ANALYZE FACTORS THAT INFLUENCE THE NUMBER OF TUBERCULOSIS CASES IN JAVA

open access: yesBarekeng, 2023
Tuberculosis is an infectious disease and one of the world's top 10 highest causes of mortality in Indonesia. Based on this fact, it is necessary to study what factors affect number of tuberculosis cases.
Yekti Widyaningsih   +1 more
doaj   +1 more source

A Bayesian zero-inflated negative binomial regression model for the integrative analysis of microbiome data. [PDF]

open access: yesBiostatistics, 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

Multiple inflated negative binomial regression for correlated multivariate count data

open access: yesDependence Modeling, 2022
This article aims to provide a method of regression for multivariate multiple inflated count responses assuming the responses follow a negative binomial distribution.
Mathews Joseph   +3 more
doaj   +1 more source

A comparison of statistical methods for modeling count data with an application to hospital length of stay

open access: yesBMC Medical Research Methodology, 2022
Background Hospital length of stay (LOS) is a key indicator of hospital care management efficiency, cost of care, and hospital planning. Hospital LOS is often used as a measure of a post-medical procedure outcome, as a guide to the benefit of a treatment
Gustavo A. Fernandez   +1 more
doaj   +1 more source

Comparison of different statistical models for the analysis of fracture events: findings from the Prevention of Falls Injury Trial (PreFIT)

open access: yesBMC Medical Research Methodology, 2023
Background Fractures are rare events and can occur because of a fall. Fracture counts are distinct from other count data in that these data are positively skewed, inflated by excess zero counts, and events can recur over time.
Anower Hossain   +5 more
doaj   +1 more source

Home - About - Disclaimer - Privacy