Results 1 to 10 of about 25,265 (258)

Using observation-level random effects to model overdispersion in count data in ecology and evolution [PDF]

PeerJ, 2014
Overdispersion is common in models of count data in ecology and evolutionary biology, and can occur due to missing covariates, non-independent (aggregated) data, or an excess frequency of zeroes (zero-inflation).
Xavier A. Harrison
doaj   +4 more sources

A STUDY OF SMALL AREA ESTIMATION TO MEASURE MULTIDIMENSIONAL POVERTY WITH MIXED MODEL POISSON, ZIP, AND ZINB

Barekeng, 2023
The research began with calculating the value of multidimensional poverty at the district level in West Java Province from SUSENAS 2021. The calculation of multidimensional poverty was based on individuals in each district or city household.
Satria June Adwendi, Asep Saefuddin, Budi Susetyo   +2 more
doaj   +1 more source

A comparison of observation-level random effect and Beta-Binomial models for modelling overdispersion in Binomial data in ecology & evolution [PDF]

PeerJ, 2015
Overdispersion is a common feature of models of biological data, but researchers often fail to model the excess variation driving the overdispersion, resulting in biased parameter estimates and standard errors.
Xavier A. Harrison
doaj   +2 more sources

Monitoring overdispersed process in clinical laboratories using control charts

Dyna, 2022
Overdispersion is a phenomenon that generally occurs in the analysis of large sample sizes. In discrete data analysis, it refers to the presence of a variation higher than that implied by a reference Binomial or Poisson distributions.
José I. Valdés-Manuel, Juan M. Cogollo-Flórez   +1 more
doaj   +1 more source

New statistical process control charts for overdispersed count data based on the Bell distribution [PDF]

Anais da Academia Brasileira de Ciências, 2023
Poisson distribution is a popular discrete model used to describe counting information, from which traditional control charts involving count data, such as the c and u charts, have been established in the literature.
LAION L. BOAVENTURA, PAULO H. FERREIRA, ROSEMEIRE L. FIACCONE, PEDRO L. RAMOS, FRANCISCO LOUZADA   +4 more
doaj   +1 more source

COVID-19 hospitalizations and patients' age at admission: The neglected importance of data variability for containment policies

Frontiers in Public Health, 2022
IntroductionAn excess in the daily fluctuation of COVID-19 in hospital admissions could cause uncertainty and delays in the implementation of care interventions.
Danila Azzolina, Danila Azzolina, Rosanna Comoretto, Rosanna Comoretto, Corrado Lanera, Paola Berchialla, Ileana Baldi, Dario Gregori   +7 more
doaj   +1 more source

Adjusting for overdispersion in piecewise exponential regression models to estimate excess mortality rate in population-based research

BMC Medical Research Methodology, 2016
Background In population-based cancer research, piecewise exponential regression models are used to derive adjusted estimates of excess mortality due to cancer using the Poisson generalized linear modelling framework.
Miguel Angel Luque-Fernandez, Aurélien Belot, Manuela Quaresma, Camille Maringe, Michel P. Coleman, Bernard Rachet   +5 more
doaj   +1 more source

Modelling zero-truncated overdispersed antenatal health care count data of women in Bangladesh.

PLoS ONE, 2020
Overdispersion in count data analysis is very common in many practical fields of health sciences. Ignorance of the presence of overdispersion in such data analysis may cause misleading inferences and thus lead to incorrect interpretations of the results.
Zakir Hossain, Rozina Akter, Nasrin Sultana, Enamul Kabir   +3 more
doaj   +1 more source

Overdispersion study of poisson and zero-inflated poisson regression for some characteristics of the data on lamda, n, p

IJAIN (International Journal of Advances in Intelligent Informatics), 2016
Poisson distribution is one of discrete distribution that is often used in modeling of rare events. The data obtained in form of counts with non-negative integers. One of analysis that is used in modeling count data is Poisson regression.
Lili Puspita Rahayu, Kusman Sadik, Indahwati Indahwati   +2 more
doaj   +1 more source

PENERAPAN REGRESI ZERO-INFLATED NEGATIVE BINOMIAL (ZINB) UNTUK PENDUGAAN KEMATIAN ANAK BALITA

E-Jurnal Matematika, 2013
One method of regression analysis used to analyze the count data is Poisson regression. Poisson regression requires that the mean value equal to the value of variance (equidispersion).
NI MADE SEKARMINI, I KOMANG GDE SUKARSA, I GUSTI AYU MADE SRINADI   +2 more
doaj   +1 more source