Results 41 to 50 of about 9,896 (146)

A Comparison of the Robust Zero-Inflated and Hurdle Models with an Application to Maternal Mortality

Mathematical and Computational Applications
This study evaluates the performance of count regression models in the presence of zero inflation, outliers, and overdispersion using both simulated and real-world maternal mortality dataset.
Phelo Pitsha, Raymond T. Chiruka, Chioneso S. Marange   +2 more
doaj   +1 more source

Predicting cyanobacteria abundance with Bayesian zero-inflated models

Journal of Hydroinformatics, 2023
Cyanobacterial blooms are a persistent concern to water management and treatment, with blooms potentially causing the release of toxins and degrading water quality.
Yirao Zhang, Nicolas M. Peleato
doaj   +1 more source

Robustness of zero-augmented models over generalized linear models in analysing fertility data in Nigeria

BMC Research Notes, 2019
Objective Fertility is a count data usually rightly skewed and exhibiting large number of zeros than the distributional assumption of the generalized linear models (GLMs).
Yusuf Olushola Kareem, Imran O. Morhason-Bello, Ayo Stephen Adebowale, Joshua Odunayo Akinyemi, Oyindamola Bidemi Yusuf   +4 more
doaj   +1 more source

Finding the Right Distribution for Highly Skewed Zero-inflated Clinical Data

Epidemiology, Biostatistics and Public Health, 2013
Discrete, highly skewed distributions with excess numbers of zeros often result in biased estimates and misleading inferences if the zeros are not properly addressed.
Resmi Gupta, Bradley S. Marino, James F Cnota, Richard F Ittenbach   +3 more
doaj   +1 more source

Modeling the distribution of new MRI cortical lesions in multiple sclerosis longitudinal studies. [PDF]

PLoS ONE, 2011
ObjectiveRecent studies have shown the relevance of the cerebral grey matter involvement in multiple sclerosis (MS). The number of new cortical lesions (CLs), detected by specific MRI sequences, has the potential to become a new research outcome in ...
Maria Pia Sormani, Massimiliano Calabrese, Alessio Signori, Antonio Giorgio, Paolo Gallo, Nicola De Stefano   +5 more
doaj   +1 more source

Weather based forewarning model for cotton pests using zero-inflated and hurdle regression models

Journal of Agrometeorology
Early forewarning of crop pest based on weather variables provides lead time to manage impending pest attacks that minimize crop loss, decrease the cost of pesticides and enhance the crop yield.
N. NARANAMMAL, S.R. KRISHNA PRIYA
doaj   +1 more source

Zero-inflated models for the evaluation of colorectal polyps in colon cancer screening studies—a value-based biostatistics practice [PDF]

PeerJ
Background Colon cancer screening studies are needed for the early detection of colorectal polyps to reduce the risk of colorectal cancer. Unfortunately, the data generated on colon polyps are typically analyzed in their dichotomized form and sometimes ...
Alok K. Dwivedi, Sherif E. Elhanafi, Mohamed O. Othman, Marc J. Zuckerman   +3 more
doaj   +2 more sources

PEMODELAN DATA TERSENSOR KANAN MENGGUNAKAN ZERO INFLATED NEGATIVE BINOMIAL DAN HURDLE NEGATIVE BINOMIAL

Indonesian Journal of Statistics and Its Applications, 2019
Health is a very important thing for humanity. One way to look at a person's health condition is through the number of unhealthy days which can also shows the productivity of the community in a region. Modeling the number of unhealthy days which are examples of count data can be done using Poisson regression.
Kusni Rohani Rumahorbo, Budi Susetyo, Kusman Sadik   +2 more
openaire   +2 more sources

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

BMC 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, Kristina P. Vatcheva   +1 more
doaj   +1 more source

Modeling sparse Rift Valley fever incidence data: a Bayesian perspective on zero-inflated self-exciting and autoregressive models

BMC Infectious Diseases
Background Rift Valley fever (RVF) is a mosquito-borne zoonotic disease for which predictive modeling is often hindered by sparse data, particularly the high frequency of zero counts in both human and livestock surveillance systems.
Alexandros Angelakis, Bryan O. Nyawanda, Penelope Vounatsou   +2 more
doaj   +1 more source