• Journal of Technology Innovation
• /
• v.14 no.3
• /
• pp.23-42
• /
• 2006

This study investigates the determinants of output of a manufacturing firm's innovative activity (the number of patent applications) and spillover effects using a count data model. This paper attempted a negative binomial distribution In order to take into account unobserved heterogeneity. The results of our study suggested that Firm size, R&D intensity, technical network activity, and online business performance have significantly positive effects in the Korean manufacturing industry. Moreover, there are significantly positive spillover effects in the same industry sector.

• Journal of the Korean Data and Information Science Society
• /
• v.26 no.2
• /
• pp.387-397
• /
• 2015

In this paper, the determinants of the number of job changes in the SMEs (small and medium enterprises) youth-intern project is analysed, utilizing SMEs youth-intern DB and employment insurance DB. Since the number of job changes are count data which take integer values other than negative values, general linear regression analysis becomes inappropriate. Therefore, four models such as Poisson regression model, zero inflated Poisson regression model, negative binomial regression model and zero inflated negative binomial regression model are tried to fit count data. A zero inflated negative binomial regression model is selected to be the best model. Major results are the followings. First, the number of job changes is shown to be significantly smaller in the treatment group than in the control group. Second, the number of job changes turns out to be significantly smaller in the young-age group than in the old-age group. Third, it is also shown that the number of job changes of man is significantly greater than that of woman. Lastly, the number of job changes in the bigger firm is shown to be significantly less than that of the smaller firm.

• The Korean Journal of Applied Statistics
• /
• v.8 no.2
• /
• pp.147-161
• /
• 1995

The primary objective of this paper is to review parametric models and test statistics related to overdspersion of count data. Poisson or binomial assumption often fails to explain overdispersion. We reviewed real examples of overdispersion in count data that occurred in toxicological or teratological experiments. We also reviewed several models that were suggested for implementing experiments. We also reviewed several models that were suggested for implementing the extra-binomial variation or hyper-Poisson variability, and we noted how these models were generalized and further developed. The approaches that have been suggested for the overdispersion fall into two broad categories. The one is to develop a parametric model for it, and the other is to assume a particular relationship between the variance and the mean of the response variable and to derive a score test staistics for detecting the overdispersion. Recently, Dean(1992) derived a general score test statistics for detecting overdispersion from the exponential family.

• The Journal of Fisheries Business Administration
• /
• v.43 no.2
• /
• pp.41-49
• /
• 2012

This study aimed to estimate the economic value of the recreational fishing in the Jeonnam marine ranching area as a part of the total socioeconomic evaluation of the Jeonnam marine ranching program. A travel cost method was applied to the estimation of economic value of the recreational fishing in the Jeonnam marine ranching area and input variables included annual fishing trip days, average travel cost per trip, average catch amount, monthly income, marriage, age, and personal perception on the marine ranching program. In the analysis, due to its characteristic of count data, both poisson model and negative binomial model were used. Model results indicated that a negative binomial model was statistically more suitable than the poisson model as the overdispersion problem occurred in the poisson model. All signs of the estimated parameters were estimated as previous studies showed. Based on the results, the economic value per trip of the recreational fishing in the Jeonnam marine ranching area was estimated to be 145,000 won and the annual total economic value of the recreational fishing in the Jeonnam marine ranching area was analyzed to be 2,514,000 won. In addition, the change of total value by catch rate showed that the economic value could be increased by 180,900 won as the catch increased by one kilogram.

• Communications for Statistical Applications and Methods
• /
• v.7 no.1
• /
• pp.269-276
• /
• 2000

there are several methods available for estimating parameters in overdispersed binary response data with the litter effect. Simulations are performed to compare methods for estimating an overall mean and an overdispersion parameter using moments a maximum likelihood under a beta-binomial distribution a maximum quasi-likelihood and a maximum extended quasi-likelihood.

• Environmental and Resource Economics Review
• /
• v.27 no.3
• /
• pp.545-567
• /
• 2018

This study applied and compared Poisson model, negative binomial model, zero inflated Poisson model, and zero inflated negative binomial model to estimate determinants of employed labour quantity. To estimate each of models, this study used fisheries census data which were obtained at microdata integrated service running by Statistics Korea. The study selected zero inflated negative binomial model according to the Vuong test and Likelihood-ratio test. In addition, the study estimated fishing village's practical changes on employed labour quantity as analyzing changes from 2010 to 2015. The results showed that the household with fishing vessels and high selling price had a significant effect on decrease of the labour quantities. Meanwhile, the longer work experience of the household, the more significant the increase in the labour quantities. In conclusion, this study presented that capitalized fishing household and the acceleration of aging had a significant impact on the change in the labour quantities.

• Journal of Korean Academy of Nursing
• /
• v.44 no.6
• /
• pp.743-750
• /
• 2014

Purpose: The objective of this study was to provide a trend analysis of the prevalence of diabetes relative to the socioeconomic, lifestyle, and physiologic risk factors among Korean adults aged over 30 years for a 10-year period using data from the Korean National Health and Nutrition Examination Survey. Methods: Prevalence difference and the slope index of inequality were calculated for each risk factors using binomial regression by considering the repeated cross-sectional features of the data. The prevalence ratio and the relative index of inequality were calculated using log-binomial regression. Linear trend tests were performed using SAS 9.2. Results: Crude prevalence of diabetes increased over the 10-year period, and was higher for men than for women. It was very high for adults 60 years or over, consistently increasing over time. The prevalence among unemployed men, women with higher level of stress, women with hypertension, and adults with serum triglyceride levels over 135 mg/dL increased over the 10-year period in comparison with the respective control group. Conclusion: Considering the rapid economic development and associated lifestyle changes in Korea, action should be taken to control the prevalence of diabetes by both preventing and consistently monitoring these identified risk factors using a public-health approach.

• International Journal of Highway Engineering
• /
• v.16 no.4
• /
• pp.111-118
• /
• 2014

PURPOSES: The purposes are to analyze the pedestrian accident severity and to develop the accident models by arterial road function. METHODS: To analyze the accident, count data and ordered logit models are utilized in this study. In pursuing the above, this study uses pedestrian accident data from 2007 to 2011 in Cheongju. RESULTS : The main results are as follows. First, daytime, Tue.Wed.Thu., over-speeding, male pedestrian over 65 old are selected as the independent variables to increase pedestrian accident severity. Second, as the accident models of main and minor arterial roads, the negative binomial models are developed, which are analyzed to be statistically significant. Third, such the main variables related to pedestrian accidents as traffic and pedestrian volume, road width, number of exit/entry are adopted in the models. Finally, Such the policy guidelines as the installation of pedestrian fence, speed hump and crosswalks with pedestrian refuge area, designated pedestrian zone, and others are suggested for accident reduction. CONCLUSIONS: This study analyzed the pedestrian accident severity, and developed the negative binomial accident models. The results of this study expected to give some implications to the pedestrian safety improvement in Cheongju.

• The Korean Journal of Applied Statistics
• /
• v.21 no.4
• /
• pp.603-613
• /
• 2008

We often encounter the situation that discrete count data have a large portion of zeros. In this case, it is not appropriate to analyze the data based on standard regression models such as the poisson or negative binomial regression models. In this article, we consider Bayesian analysis for two commonly used models. They are zero-inflated poisson and negative binomial regression models. We use the Bayes factor as a model selection tool and computation is proceeded via Markov chain Monte Carlo methods. Crash count data are analyzed to support theoretical results.

• The Korean Journal of Applied Statistics
• /
• v.24 no.5
• /
• pp.951-961
• /
• 2011

In this paper, we propose a Bayesian inference using the Markov Chain Monte Carlo(MCMC) method for the zero inflated negative binomial(ZINB) regression model. The proposed model allows the regression model for zero inflation probability as well as the regression model for the mean of the dependent variable. This extends the work of Jang et al. (2010) to the fully defiend ZINB regression model. In addition, we apply the proposed method to a real data example, and compare the efficiency with the zero inflated Poisson model using the DIC. Since the DIC of the ZINB is smaller than that of the ZIP, the ZINB model shows superior performance over the ZIP model in zero inflated count data with overdispersion.