Results 11 to 20 of about 15,347,884 (286)
Double Generalized Beta-Binomial and Negative Binomial Regression Models [PDF]
Revista Colombiana de Estadística, 2017 Overdispersion is a common phenomenon in count datasets, that can greatly affect inferences about the model. In this paper develop three joint mean and dispersion regression models in order to fit overdispersed data.
EDILBERTO CEPEDA-CUERVO +1 more
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Bootstrap goodness-of-fit test for the beta-binomial model [PDF]
Journal of Applied Statistics, 2001 A common question in the analysis of binary data is how to deal with overdispersion. One widely advocated sampling distribution for overdispersed binary data is the beta-binomial model. For example, this distribution is often used to model litter effects in toxicological experiments.
Piegorsch, Walter +2 more
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Longitudinal beta‐binomial modeling using GEE for overdispersed binomial data [PDF]
Statistics in Medicine, 2016 Longitudinal binomial data are frequently generated from multiple questionnaires and assessments in various scientific settings for which the binomial data are often overdispersed. The standard generalized linear mixed effects model may result in severe underestimation of standard errors of estimated regression parameters in such cases and hence ...
Wu, Hongqian +2 more
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Beta-binomial model for meta-analysis of odds ratios. [PDF]
Stat Med, 2017 In meta‐analysis of odds ratios (ORs), heterogeneity between the studies is usually modelled via the additive random effects model (REM). An alternative, multiplicative REM for ORsuses overdispersion. The multiplicative factor in this overdispersion model (ODM) can be interpreted as an intra‐class correlation (ICC) parameter.
Bakbergenuly I, Kulinskaya E.
europepmc +7 more sources
A Zero-inflated Beta-binomial Model for Microbiome Data Analysis. [PDF]
Stat (Int Stat Inst), 2018 The Microbiome is increasingly recognized as an important aspect of the health of host species, involved in many biological pathways and processes and potentially useful as health biomarkers. Taking advantage of high‐throughput sequencing technologies, modern bacterial microbiome studies are metagenomic, interrogating thousands of taxa simultaneously ...
Hu T, Gallins P, Zhou YH.
europepmc +5 more sources
Empirical-distribution-function Tests for the Beta-Binomial Model
Journal of Applied Statistics, 2007 Abstract Empirical-distribution-function (EDF) goodness-of-fit tests are considered for the beta-binomial model. The testing procedures based on EDF statistics are given. A Monte Carlo study is conducted to investigate the accuracy and power of the tests against various alternative distributions.
Chien-Tai Lin, Cheng-Chieh Chou
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Beta-Binomial Model for Count Data: An Application in Estimating Model-Based Oral Reading Fluency. [PDF]
Educ Psychol MeasIn this article, the beta-binomial model for count data is proposed and demonstrated in terms of its application in the context of oral reading fluency (ORF) assessment, where the number of words read correctly (WRC) is of interest.
Qiao X +4 more
europepmc +2 more sources
The Beta-Binomial Distribution [PDF]
, 2023 The beta-binomial distribution can be thought of as a binomial distribution where the probability of success in each trial is not fixed but follows a beta distribution. It is often used to capture correlation in a sequence of Bernoulli trials or to model
Hodel, Florian, Booth, James
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BETA-BINOMIAL MODEL IN SMALL AREA ESTIMATION USING HIERARCHICAL LIKELIHOOD APPROACH
Media Statistika, 2023 Small Area Estimation is a statistical method used to estimate parameters in sub-populations with small or even no sample sizes. This research aims to evaluate the Beta-Binomial model's performance for estimating small areas at the area level.
Etis Sunandi +3 more
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Multiplicative-Binomial Distribution: Some Results on Characterization, Inference and Random Data Generation [PDF]
Journal of Statistical Theory and Applications (JSTA), 2013 Multiplicative-binomial distribution is one of the distributions that allows for over-dispersion and under-dispersion relative to the standard binomial distribution.
Elsayed A.H. Elamir
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