Macroeconomic Determinants, Innovation and the Birth of New Firms: Negative Binomial Regression Approach

This article addresses on an aspect of firms internationalization so far little explored, the choice of the number of export destinations and a proxy of the complexity of the export activity. As the outcome variable is a count with an excess of zeros, we use a hurdle regression model for count data that also allow disentangling the aspect of heterogeneity related to the decision to export from those measuring the number of markets served. Some differences arise by the comparison between the estimates regarding the propensity to export model and those of the model describing the number of export destinations. Regarding the propensity to export, the estimated models support the familiar evidences already presented in literature: exporters are larger, more productive, more innovative and invest more. With reference to the number of export destinations, it seems that not only the larger the number of markets served the more productive, large and willing to invest is the firm but also firms engaged in multiple markets seem to be older, financially stable, and willing to support organizational and managerial innovations.

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Generalized ridge estimator in negative binomial regression model

Journal of Physics Conference Series ◽

10.1088/1742-6596/1897/1/012019 ◽

2021 ◽

Vol 1897 (1) ◽

pp. 012019

Author(s):

Nadwa Khazaal Rashad ◽

Nawal Mahmood Hammood ◽

Zakariya Yahya Algamal

Keyword(s):

Regression Model ◽

Negative Binomial ◽

Negative Binomial Regression ◽

Negative Binomial Regression Model ◽

Ridge Estimator ◽

Binomial Regression ◽

Generalized Ridge Estimator

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Is area deprivation associated with greater impacts of COVID-19 in care homes across England? A preliminary analysis of COVID-19 outbreaks and deaths

Journal of Epidemiology & Community Health ◽

10.1136/jech-2020-215039 ◽

2021 ◽

pp. jech-2020-215039 ◽

Cited By ~ 2

Author(s):

Anders Malthe Bach-Mortensen ◽

Michelle Degli Esposti

Keyword(s):

Negative Binomial ◽

Care Home ◽

Negative Binomial Regression ◽

Population Characteristics ◽

Care Homes ◽

Future Research ◽

Area Deprivation ◽

Binomial Regression ◽

Index Of Multiple Deprivation

IntroductionThe COVID-19 pandemic has disproportionately impacted care homes and vulnerable populations, exacerbating existing health inequalities. However, the role of area deprivation in shaping the impacts of COVID-19 in care homes is poorly understood. We examine whether area deprivation is linked to higher rates of COVID-19 outbreaks and deaths among care home residents across upper tier local authorities in England (n=149).MethodsWe constructed a novel dataset from publicly available data. Using negative binomial regression models, we analysed the associations between area deprivation (Income Deprivation Affecting Older People Index (IDAOPI) and Index of Multiple Deprivation (IMD) extent) as the exposure and COVID-19 outbreaks, COVID-19-related deaths and all-cause deaths among care home residents as three separate outcomes—adjusting for population characteristics (size, age composition, ethnicity).ResultsCOVID-19 outbreaks in care homes did not vary by area deprivation. However, COVID-19-related deaths were more common in the most deprived quartiles of IDAOPI (incidence rate ratio (IRR): 1.23, 95% CI 1.04 to 1.47) and IMD extent (IRR: 1.16, 95% CI 1.00 to 1.34), compared with the least deprived quartiles.DiscussionThese findings suggest that area deprivation is a key risk factor in COVID-19 deaths among care home residents. Future research should look to replicate these results when more complete data become available.

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Association between fatality rate of COVID-19 and selenium deficiency in China

BMC Infectious Diseases ◽

10.1186/s12879-021-06167-8 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Hai-Yang Zhang ◽

An-Ran Zhang ◽

Qing-Bin Lu ◽

Xiao-Ai Zhang ◽

Zhi-Jie Zhang ◽

...

Keyword(s):

Negative Binomial ◽

Viral Infections ◽

Case Fatality ◽

Selenium Deficiency ◽

Negative Binomial Regression ◽

Negative Binomial Regression Model ◽

Fatality Rate ◽

Selenium Content ◽

Individual Level ◽

Binomial Regression

Abstract Background COVID-19 has impacted populations around the world, with the fatality rate varying dramatically across countries. Selenium, as one of the important micronutrients implicated in viral infections, was suggested to play roles. Methods An ecological study was performed to assess the association between the COVID-19 related fatality and the selenium content both from crops and topsoil, in China. Results Totally, 14,045 COVID-19 cases were reported from 147 cities during 8 December 2019–13 December 2020 were included. Based on selenium content in crops, the case fatality rates (CFRs) gradually increased from 1.17% in non-selenium-deficient areas, to 1.28% in moderate-selenium-deficient areas, and further to 3.16% in severe-selenium-deficient areas (P = 0.002). Based on selenium content in topsoil, the CFRs gradually increased from 0.76% in non-selenium-deficient areas, to 1.70% in moderate-selenium-deficient areas, and further to 1.85% in severe-selenium-deficient areas (P < 0.001). The zero-inflated negative binomial regression model showed a significantly higher fatality risk in cities with severe-selenium-deficient selenium content in crops than non-selenium-deficient cities, with incidence rate ratio (IRR) of 3.88 (95% CIs: 1.21–12.52), which was further confirmed by regression fitting the association between CFR of COVID-19 and selenium content in topsoil, with the IRR of 2.38 (95% CIs: 1.14–4.98) for moderate-selenium-deficient cities and 3.06 (1.49–6.27) for severe-selenium-deficient cities. Conclusions Regional selenium deficiency might be related to an increased CFR of COVID-19. Future studies are needed to explore the associations between selenium status and disease outcome at individual-level.

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Statistical models for analyzing count data: predictors of length of stay among HIV patients in Portugal using a multilevel model

BMC Health Services Research ◽

10.1186/s12913-021-06389-1 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Ahmed Nabil Shaaban ◽

Bárbara Peleteiro ◽

Maria Rosario O. Martins

Keyword(s):

Length Of Stay ◽

Regression Model ◽

Random Effects ◽

Count Data ◽

Negative Binomial ◽

Negative Binomial Regression ◽

Comprehensive Approach ◽

Negative Binomial Regression Model ◽

Hiv Patients ◽

Binomial Regression

Abstract Background This study offers a comprehensive approach to precisely analyze the complexly distributed length of stay among HIV admissions in Portugal. Objective To provide an illustration of statistical techniques for analysing count data using longitudinal predictors of length of stay among HIV hospitalizations in Portugal. Method Registered discharges in the Portuguese National Health Service (NHS) facilities Between January 2009 and December 2017, a total of 26,505 classified under Major Diagnostic Category (MDC) created for patients with HIV infection, with HIV/AIDS as a main or secondary cause of admission, were used to predict length of stay among HIV hospitalizations in Portugal. Several strategies were applied to select the best count fit model that includes the Poisson regression model, zero-inflated Poisson, the negative binomial regression model, and zero-inflated negative binomial regression model. A random hospital effects term has been incorporated into the negative binomial model to examine the dependence between observations within the same hospital. A multivariable analysis has been performed to assess the effect of covariates on length of stay. Results The median length of stay in our study was 11 days (interquartile range: 6–22). Statistical comparisons among the count models revealed that the random-effects negative binomial models provided the best fit with observed data. Admissions among males or admissions associated with TB infection, pneumocystis, cytomegalovirus, candidiasis, toxoplasmosis, or mycobacterium disease exhibit a highly significant increase in length of stay. Perfect trends were observed in which a higher number of diagnoses or procedures lead to significantly higher length of stay. The random-effects term included in our model and refers to unexplained factors specific to each hospital revealed obvious differences in quality among the hospitals included in our study. Conclusions This study provides a comprehensive approach to address unique problems associated with the prediction of length of stay among HIV patients in Portugal.

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Association between breakfast skipping and metabolic outcomes by sex, age, and work status stratification

Nutrition & Metabolism ◽

10.1186/s12986-020-00526-z ◽

2021 ◽

Vol 18 (1) ◽

Author(s):

Jun Heo ◽

Won-Jun Choi ◽

Seunghon Ham ◽

Seong-Kyu Kang ◽

Wanhyung Lee

Keyword(s):

Regression Analysis ◽

Negative Binomial ◽

Metabolic Diseases ◽

Young Male ◽

Negative Binomial Regression ◽

Final Analysis ◽

Work Status ◽

Breakfast Skipping ◽

Metabolic Outcomes ◽

Binomial Regression

Abstract Background The association between breakfast skipping and abnormal metabolic outcomes remains controversial. A comprehensive study with various stratified data is required. Objective The aim of this study was to investigate the relationship between abnormal metabolic outcomes and breakfast skipping by sex, age, and work status stratification. Methods We used data from the Korea National Health and Nutrition Examination Surveys from 2013 to 2018. A total of 21,193 (9022 men and 12,171 women) participants were included in the final analysis. The risk of metabolic outcomes linked to breakfast skipping was estimated using the negative binomial regression analysis by sex, work status, and age stratification. Results A total of 11,952 (56.4%) participants consumed breakfast regularly. The prevalence of abnormal metabolic outcomes was higher among those with irregular breakfast consumption habits. Among young male workers, negative binomial regression analysis showed that irregular breakfast eaters had a higher risk of abnormal metabolic outcomes, after adjusting for covariates (odds ratio, 1.15; 95% confidence interval, 1.03–1.27). Conclusions The risk of abnormal metabolic outcomes was significant in young men in the working population. Further studies are required to understand the association of specific working conditions (working hours or shift work) with breakfast intake status and the risk of metabolic diseases.

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