Results 101 to 110 of about 205,844 (216)

The Association of Demographic and Clinical Factors with the Frequency of Restenosis in Patients Undergoing Angioplasty Using Negative Binomial Regression

مجله اپیدمیولوژی ایران, 2016
Background and Objectives: One of the main concerns of heart specialists is the occurrence of restenosis after coronary angioplasty which can lead to coronary artery bypass graft, myocardial infarction, and death.
J Nasseryan, E Hajizadeh, A Rasekhi, H Ahangar   +3 more
doaj  

Marginal modeling in community randomized trials with rare events: Utilization of the negative binomial regression model. [PDF]

Clin Trials, 2022
Westgate PM, Cheng DM, Feaster DJ, Fernández S, Shoben AB, Vandergrift N.   +5 more
europepmc   +1 more source

Hermite regression analysis of multi-modal count data [PDF]

We discuss the modeling of count data whose empirical distribution is both multi-modal and over-dispersed, and propose the Hermite distribution with covariates introduced through the conditional mean. The model is readily estimated by maximum likelihood,
David E Giles
core  

A four-parameter negative binomial-Lindley regression model to analyze factors influencing the number of cancer deaths using Bayesian inference

, 2023

openalex   +1 more source

New robust estimators for the fixed effects negative binomial model: a simulation and real-world applications to European panel data

Frontiers in Applied Mathematics and Statistics
This study introduces a more flexible approach by employing the fixed effects negative binomial model to address challenges associated with outliers and dispersion.
Mohamed R. Abonazel, Ehab Ebrahim Mohamed Ebrahim, Elsayed G. Ahmed, Amera M. El-Masry   +3 more
doaj   +1 more source

Bayesian negative binomial regression model with unobserved covariates for predicting the frequency of north atlantic tropical storms. [PDF]

J Appl Stat, 2023
Li X, Ghosh J, Villarini G.
europepmc   +1 more source

Clarify: Software for Interpreting and Presenting Statistical Results [PDF]

Clarify is a program that uses Monte Carlo simulation to convert the raw output of statistical procedures into results that are of direct interest to researchers, without changing statistical assumptions or requiring new statistical models.
Gary King, Jason Wittenberg, Micahael Tomz   +2 more
core   +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

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

Biostatistics, 2021
Jiang S, Xiao G, Koh AY, Kim J, Li Q, Zhan X.   +5 more
europepmc   +1 more source

Recreational Demand for Equestrian Trail-Riding [PDF]

Using data collected from a combination of on-site and on-line surveys, this study examines recreational demand for equestrian trail-riding in Kentucky.
Auchter, Katharine, Blackwell, Melanie, Hu, Wuyang, Pagoulatos, Angelos   +3 more
core   +1 more source