Correction to: Gomes, A.E., da-Silva, C., Cordeiro, G.M. (2015). The exponentiated G Poisson model. Communications in Statistics - Theory and Methods, 44:20, 4217-4240

Abstract We estimate a travel cost model for the George Washington & Jefferson National Forests using an On-Site Latent Class Poisson Model. We show that the constraints of ad-hoc truncation and homogenous preferences significantly impact consumer surplus estimates derived from the on-site travel cost model. By relaxing the constraints, we show that more than one class of visitors with unique preferences exists in the population. The resulting demand functions, price responsive behaviors, and consumer surplus estimates reflect differences across these classes of visitors. With heterogeneous preferences, a group of ‘local residents’ exists with a probability of 8% and, on average take 113 visits.

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Comparing Bayesian Spatial Conditional Overdispersion and the Besag–York–Mollié Models: Application to Infant Mortality Rates

Mathematics ◽

10.3390/math9030282 ◽

2021 ◽

Vol 9 (3) ◽

pp. 282

Author(s):

Mabel Morales-Otero ◽

Vicente Núñez-Antón

Keyword(s):

Infant Mortality ◽

Count Data ◽

Spatial Dependence ◽

Poisson Model ◽

Mortality Rates ◽

Estimation Methods ◽

Neighborhood Structure ◽

Specific Context ◽

Count Data Models ◽

Conditional Mean

In this paper, we review overdispersed Bayesian generalized spatial conditional count data models. Their usefulness is illustrated with their application to infant mortality rates from Colombian regions and by comparing them with the widely used Besag–York–Mollié (BYM) models. These overdispersed models assume that excess of dispersion in the data may be partially caused from the possible spatial dependence existing among the different spatial units. Thus, specific regression structures are then proposed both for the conditional mean and for the dispersion parameter in the models, including covariates, as well as an assumed spatial neighborhood structure. We focus on the case of response variables following a Poisson distribution, specifically concentrating on the spatial generalized conditional normal overdispersion Poisson model. Models were fitted by making use of the Markov Chain Monte Carlo (MCMC) and Integrated Nested Laplace Approximation (INLA) algorithms in the specific context of Bayesian estimation methods.

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Intra-urban differentials of congenital and acquired syphilis and syphilis in pregnant women in an urban area in northeastern Brazil

Transactions of the Royal Society of Tropical Medicine and Hygiene ◽

10.1093/trstmh/trab011 ◽

2021 ◽

Author(s):

Talita Araujo de Souza ◽

Karen Kaline Teixeira ◽

Reginaldo Lopes Santana ◽

Cinthia Barros Penha ◽

Arthur de Almeida Medeiros ◽

...

Keyword(s):

Relative Risk ◽

Pregnant Women ◽

Congenital Syphilis ◽

Kernel Density ◽

Poisson Model ◽

Northeastern Brazil ◽

Smoothing Function ◽

Density Estimator ◽

Epidemic Disease ◽

Peripheral Areas

Abstract Background Currently syphilis is considered an epidemic disease worldwide. The objective of this study was to identify intra-urban differentials in the occurrence of congenital and acquired syphilis and syphilis in pregnant women in the city of Natal, in northeast Brazil. Methods Cases of syphilis recorded by the municipal surveillance system from 1 January 2011 to 30 December 2018 were analysed. Spatial statistical analyses were performed using the kernel density estimator of the quadratic smoothing function (weighted). SaTScan software was applied for the calculation of risk based on a discrete Poisson model. Results There were 2163 cases of acquired syphilis, 738 cases of syphilis in pregnant women and 1279 cases of congenital syphilis. Kernel density maps showed that the occurrence of cases is more prevalent in peripheral areas and in areas with more precarious urban infrastructure. In 2011–2014 and 2015–2018, seven statistically significant clusters of acquired syphilis were identified. From 2011 to 2014, the most likely cluster had a relative risk of 3.54 (log likelihood ratio [LLR] 38 895; p<0.001) and from 2015 to 2018 the relative risk was 0.54 (LLR 69 955; p<0.001). Conclusions In the municipality of Natal, there was a clustered pattern of spatial distribution of syphilis, with some areas presenting greater risk for the occurrence of new cases.

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Neutral-Carrier Ion-Selective Electrodes Assessed by the Nernst–Planck–Poisson Model

Analytical Chemistry ◽

10.1021/acs.analchem.5b00065 ◽

2015 ◽

Vol 87 (17) ◽

pp. 8665-8672 ◽

Cited By ~ 16

Author(s):

Jerzy J. Jasielec ◽

Tomasz Sokalski ◽

Robert Filipek ◽

Andrzej Lewenstam

Keyword(s):

Poisson Model ◽

Ion Selective Electrodes ◽

Neutral Carrier

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Migrant Women’s Help-Seeking Decisions and Use of Support Resources for Intimate Partner Violence in China

Violence Against Women ◽

10.1177/10778012211000133 ◽

2021 ◽

pp. 107780122110001

Author(s):

Ran Hu ◽

Jia Xue ◽

Xiying Wang

Keyword(s):

Intimate Partner Violence ◽

Partner Violence ◽

Help Seeking ◽

Multinomial Logistic Regression ◽

Poisson Model ◽

Intimate Partner ◽

Future Research ◽

Related Factors ◽

Cross Sectional ◽

Sources Of Support

In China, women who domestically relocate from rural or less developed regions to major cities are at a higher risk for intimate partner violence (IPV) than their non-migrant counterparts. Few studies have focused on Chinese domestic migrant women’s help-seeking for IPV and their use of different sources of support. The present study aimed to identify factors that influence migrant women’s help-seeking decisions. In addition, we also examined factors that contribute to migrant women’s use of diverse sources of support for IPV. A sample of 280 migrant women victimized by IPV in the past year at the time of the survey was drawn from a larger cross-sectional study conducted in four major urban cities in China, including Beijing, Shanghai, Guangzhou, and Shenzhen. Using a multinomial logistic regression model and a zero-inflated Poisson model, we found that factors influencing migrant women’s help-seeking decisions and their use of diverse sources of support included socioeconomic factors, IPV type, relationship-related factors, knowledge of China’s first anti-Domestic Violence Law, and perception of the effectiveness of current policies. We discuss implications for future research and interventions.

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