Search results for "overdispersion"
showing 10 items of 14 documents
Empirical Bayes improves assessments of diversity and similarity when overdispersion prevails in taxonomic counts with no covariates
2019
Abstract The assessment of diversity and similarity is relevant in monitoring the status of ecosystems. The respective indicators are based on the taxonomic composition of biological communities of interest, currently estimated through the proportions computed from sampling multivariate counts. In this work we present a novel method to estimate the taxonomic composition able to work even with a single sample and no covariates, when data are affected by overdispersion. The presence of overdispersion in taxonomic counts may be the result of significant environmental factors which are often unobservable but influence communities. Following the empirical Bayes approach, we combine a Bayesian mo…
A comparison between nine laboratories performing triangle tests
2012
WOS: 000299451400001; International audience; Fifteen groups of participants in nine laboratories performed triangle tests with two pairs of soft drinks. Groups differed in practice level with triangle tests: eight groups of 60 consumers who were not used to triangle test, three groups of qualified assessors who have already performed a few triangle tests, and four groups of trained assessors with a more extensive practice of triangle tests; qualified and trained groups included 9 or 18 assessors. The soft drinks were made from syrups at two levels of dilution in order to achieve about 55% of correct responses to test for difference and about 40% of correct responses to test for similarity.…
Spatial analysis of traffic accidents near and between road intersections in a directed linear network.
2019
Although most of the literature on traffic safety analysis has been developed over areal zones, there is a growing interest in using the specific road structure of the region under investigation, which is known as a linear network in the field of spatial statistics. The use of linear networks entails several technical complications, ranging from the accurate location of traffic accidents to the definition of covariates at a spatial micro-level. Therefore, the primary goal of this study was to display a detailed analysis of a dataset of traffic accidents recorded in Valencia (Spain), which were located into a linear network representing more than 30 km of urban road structure corresponding t…
Handling Underdispersion in Calibrating Safety Performance Function at Urban, Four-Leg, Signalized Intersections
2011
Poisson basic assumption of equidispersion is often too much restrictive for crash count data; in fact this type of data has been found to often exhibit overdispersion. Underdispersion has been less commonly observed, and this is the reason why it has been less convenient to model directly than overdispersion. Overdispersion and underdispersion are not the only issues that can be a potential source of error in specifying statistical models and that can lead to biased crash-frequency predictions; these issues can derive from data properties (temporal and spatial correlation, time-varying explanatory variables, etc.) or from methodological approach (omitted variables, functional form selectio…
Italian Deprivation Index and Dental Caries in 12-Year-Old Children: A Multilevel Bayesian Analysis
2014
Evidence from the literature has shown that people with a lower socioeconomic status enjoy less good health than people with a higher socioeconomic status. The Italian deprivation index (DI) was used with the aim to evaluate the association between the DMFT index and risk factors for dental caries, including city population and DI. The study included 4,305 12-year-old children living in 38 cities classified by demographic size as small, midsize and large. Zero-inflated negative binomial multilevel regression models were used to assess risk factors for DMFT and to address excess of zero DMFT and overdispersion through a Bayesian approach. The difference in the average level of DMFT among chi…
Assessment of Susceptibility Risk Factors for ADHD in Imaging Genetic Studies
2019
Objective: ADHD consists of a count of symptoms that often presents heterogeneity due to overdispersion and excess of zeros. Statistical inference is usually based on a dichotomous outcome that is underpowered. The main goal of this study was to determine a suited probability distribution to analyze ADHD symptoms in Imaging Genetic studies. Method: We used two independent population samples of children to evaluate the consistency of the standard probability distributions based on count data for describing ADHD symptoms. Results: We showed that the zero-inflated negative binomial (ZINB) distribution provided the best power for modeling ADHD symptoms. ZINB reveals a genetic variant, rs273342…
Can bayesian models play a role in dental caries epidemiology? Evidence from an application to the BELCAP data set
2012
Objectives The aim of this study was to show the potential of Bayesian analysis in statistical modelling of dental caries data. Because of the bounded nature of the dmft (DMFT) index, zero-inflated binomial (ZIB) and beta-binomial (ZIBB) models were considered. The effects of incorporating prior information available about the parameters of models were also shown. Methods The data set used in this study was the Belo Horizonte Caries Prevention (BELCAP) study (Bohning et al. (1999)), consisting of five variables collected among 797 Brazilian school children designed to evaluate four programmes for reducing caries. Only the eight primary molar teeth were considered in the data set. A data aug…
A Bayesian Sequential Look at u-Control Charts
2005
We extend the usual implementation of u-control charts (uCCs) in two ways. First, we overcome the restrictive (and often inadequate) assumptions of the Poisson model; next, we eliminate the need for the questionable base period by using a sequential procedure. We use empirical Bayes(EB) and Bayes methods and compare them with the traditional frequentist implementation. EB methods are somewhat easy to implement, and they deal nicely with extra-Poisson variability (and, at the same time, informally check the adequacy of the Poisson assumption). However, they still need the base period. The sequential, full Bayes approach, on the other hand, also avoids this drawback of traditional u-charts. T…
Modeling accident risk at the road level through zero-inflated negative binomial models: A case study of multiple road networks
2021
Abstract This paper presents a case study carried out in multiple cities of the Valencian Community (Spain) to determine the effect of sociodemographic and road characteristics on traffic accident risk. The analyzes are performed at the road segment level, considering the linear network representing the road structure of each city as a spatial lattice. The number of accidents observed in each road segment from 2010 to 2019 is taken as the response variable, and a zero-inflated modeling approach is considered. Count overdispersion and spatial dependence are also accounted for. Despite the complexity and sparsity of the data, the fitted models performed considerably well, with few exceptions.…
Degree course change and student performance: a mixed-effect approach
2015
This paper focuses on students credits earning speed over time and its determinants, dealing with the huge percentage of students who do not take the degree within the legal duration in the Italian University System. A new indicator for the performance of the student career is proposed on real data, concerning the cohort of students enrolled at a Faculty of the University of Palermo (followed for 7 years). The new indicator highlights a typical zero-inflated distribution and suggests to investigate the effect of the degree course (DC) change on the student career. A mixed-effect model for overdispersed data is considered, with the aim of taking into account the individual variability as wel…