• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.895-900
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• 2013

In this research, we propose a simple bivariate zero inflated negative binomial regression model with different dispersion for bivariate count data with excess zeros. An application to the demand for health services shows that the proposed model is better than existing models in terms of log-likelihood and AIC.

• Communications for Statistical Applications and Methods
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• v.18 no.5
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• pp.571-579
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• 2011

We propose a new bivariate zero-inflated negative binomial regression model to allow heterogeneous dispersions. To show the performance of our proposed model, Health Care data in Deb and Trivedi (1997) are used to compare it with the other bivariate zero-inflated negative binomial model proposed by Wang (2003) that has a common dispersion between the two response variables. This empirical study shows better results from the views of log-likelihood and AIC.

• The Korean Journal of Applied Statistics
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• v.21 no.2
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• pp.341-353
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• 2008

The bootstrap method for the score test statistic is proposed in a bivariate negative binomial distribution. The Monte Carlo study shows that the score test for testing overdispersion underestimates the nominal significance level, while the score test for "intrinsic correlation" overestimates the nominal one. To overcome this problem, we propose a bootstrap method for the score test. We find that bootstrap methods keep the significance level close to the nominal significance level for testing the hypothesis. An empirical example is provided to illustrate the results.

• The Korean Journal of Applied Statistics
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• v.23 no.3
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• pp.585-594
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• 2010

This study, investigates the effects of dispersion parameters between two response variables in zero-truncated bivariate generalized Poisson distributions. A Monte Carlo study shows that the zero-truncated bivariate Poisson and negative binomial models fit poorly wherein the zero-truncated bivariate count data has heterogeneous dispersion parameters on dependent variables. In addition, we derive the score test for testing the equality of the dispersion parameters and compare its efficiency with the likelihood ratio test.

• The Korean Journal of Applied Statistics
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• v.22 no.2
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• pp.271-280
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• 2009

For bivariate binomial data with both intra and inter-class correlation, Danaher and Hardie (2005) proposed a bivariate beta-binomial model. However, the model is limited to the situation where the intra-class correlation is strictly positive. Thus it might be seriously inadequate for data with a negative intra-class correlation. Several authors have considered generalized binomial distributions covering a wider range of intra-class correlation which could relax the possible model restrictions imposed. Among others there are the additive/multiplicative and the beta/extended beta binomial model. In this study, bivariate models of the Sarmanov (1966) type are formed by combining each of those univariate models to take care of the inter-class correlation, and are evaluated in terms of the goodness-of-fit. As a result, B-mB and B-ebB are fitted, successfully, to real data and that B-mB, which has a wider permissible range than B-ebB for the intra-class correlation is relatively preferred.

• Communications for Statistical Applications and Methods
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• v.18 no.2
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• pp.219-227
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• 2011

In this paper, we proposed a generalized bivariate negative binomial distribution allowing heterogeneous dispersions on two dependent variables based on a trivariate reduction technique. In this model, we propose the score and LR tests for testing the equality of dispersions and compare the efficiencies of the proposed tests using a Monte Carlo study. The Monte Carlo study shows that the proposed score and LR tests prove to be an efficient test for the equality of dispersions in the view of the significance level and power. However, the score test is easier to compute than the LR test and it shows a slightly better performance than the LR test from the Monte Carlo study, we suggest the use of score tests for testing the equality of dispersions on two dependent variables. In addition, an empirical example is provided to illustrate the results.

• Journal of Distribution Science
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• v.13 no.8
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• pp.97-104
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• 2015

Purpose - This study examines the positive impact of the social distance between producers and users of online content, investigating and analyzing the most popular Web content. In addition, it tries to elicit the matching effect that appears when the individuals'cultural background is consistent with social distance. Research design, data, and methodology - We collected and analyzed actual data about 4,981 videos clips on YouTube, looking at six countries in order to verify the content of this study. Based on the results of the data analysis, the study conducted behavioral measurements on popularity, social distance, culture, and user engagement. The unit of analysis was the content and we collected information about the content producers and the content records. We controlled the views, comments, likes, calendar dates, and ages in the empirical models. The data was collected in 2011, with the records coming from South Korea, Japan, China, U.S., German, and France. A total of 4,980 elements were analyzed in the model. The empirical model estimated is the bivariate negative binomial distribution (NBD) model. Results - It turns out that there is a possibility that the matching effect can be diminished by variables that reflect the psychological involvement of user engagement. This study proposes academic and practical implications based on these research results. This research shows the positive effect of social distance between users and producers on the increased performance of the online content. We find the effect of social distance to be a stronger tendency in collectivism. The collectivists follow their sense of friendship and intimacy in their culture and, the social congruence effect can be found there as well. The effect, however, could erode in a social case where users are motivated by strong intrinsic and psychological factors. In addition, user engagement complicates the process of user decision making regarding the information. Conclusions - This study examines how the differential effects of social distance caused by culture could disappear through user commitment as a complicated user motivation. Some potential implications are as follows. First, a firm in the collectivism culture has to communicate based on the social distance. In fact, most online channels do not have a function that indicates the social distance as measured by favorites or subscribers. This function could help increase the performance of the content in online channels, but this increasing effect can only be found in a collectivist culture. Based on this, the firms have to communicate and announce to users the actual social distance between users and producers. Second, firms should develop a system that discovers the social distance and culture and shows these measures to users and producers, since the congruence effect between social distance and culture is found only for low user engagement. The firms can take the advantage of the congruence effect only for the development of the social distance and culture visualized system.