• The Korean Journal of Applied Statistics
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• v.26 no.2
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• pp.267-280
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• 2013

College tuition is a significant economic, social, and political issue in Korea. We conduct a Bayesian analysis of a hierarchical model to address the factors related to college tuition based on a survey data collected by Statistics Korea. A binary response variable is selected depending on if more than 70% of tuition costs are supported by parents, and a hierarchical Probit model is constructed with areas as groups. A set of explanatory variables is selected from a factor analysis of available variables in the survey. A Markov chain Monte Carlo algorithm is used to estimate parameters. From the analysis results, income and stress are significantly related to college tuition support from parents. Parents with high income tend to support children's college tuition and students with parents' financial support tend to be mentally less stressed; subsequently, this shows that the economic status of parents significantly affects the mental health of college students. Gender, a healthy life style, and college satisfaction are not significant factors. Comparing areas in terms of the degrees of correlation between stress/income and tuition support from parents, students in Kangwon-do are the most mentally stressed when parents' support is limited; in addition, the positive correlation between parents support and income is stronger in big cities compared to provincial areas.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.10
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• pp.1558-1565
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• 2020

Objective: The objective of this study was to characterize the number of loci affecting growth traits and the distribution of single nucleotide polymorphism (SNP) effects on growth traits, and to understand the genetic architecture for growth traits in Hanwoo (Korean cattle) using genome-wide association study (GWAS), genomic partitioning, and hierarchical Bayesian mixture models. Methods: GWAS: A single-marker regression-based mixed model was used to test the association between SNPs and causal variants. A genotype relationship matrix was fitted as a random effect in this linear mixed model to correct the genetic structure of a sire family. Genomic restricted maximum likelihood and BayesR: A priori information included setting the fixed additive genetic variance to a pre-specified value; the first mixture component was set to zero, the second to 0.0001×σ²_g, the third 0.001×σ²_g, and the fourth to 0.01×σ²_g. BayesR fixed a priori information was not more than 1% of the genetic variance for each of the SNPs affecting the mixed distribution. Results: The GWAS revealed common genomic regions of 2 Mb on bovine chromosome 14 (BTA14) and 3 had a moderate effect that may contain causal variants for body weight at 6, 12, 18, and 24 months. This genomic region explained approximately 10% of the variance against total additive genetic variance and body weight heritability at 12, 18, and 24 months. BayesR identified the exact genomic region containing causal SNPs on BTA14, 3, and 22. However, the genetic variance explained by each chromosome or SNP was estimated to be very small compared to the total additive genetic variance. Causal SNPs for growth trait on BTA14 explained only 0.04% to 0.5% of the genetic variance Conclusion: Segregating mutations have a moderate effect on BTA14, 3, and 19; many other loci with small effects on growth traits at different ages were also identified.

• Asia Marketing Journal
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• v.11 no.1
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• pp.73-92
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• 2009

Consumers influence other consumers' brand choice behavior by delivering a variety of objective or subjective information on a particular product, which is called WOM (Word-Of-Mouth) activities. For WOM activities, WOM senders should choose messages to deliver to other consumers. We classify the contents of the messages a consumer chooses for WOM delivery into two categories: Subjective (positive or negative) evaluation and objective information on products. In our study, we regard WOM senders' activities as a choice behavior and introduce a choice model to study the relationship between the choice of different WOM information (WOM with positive or negative subjective evaluation and WOM with objective information) and its influencing factors (information sources and consumer characteristics) by developing two bivariate Probit models. In order to consider the mediating effects of WOM senders' product involvement, product attitude, and their characteristics (gender and age), we develop three second-level models for the propagation of positive evaluations, of negative evaluations, and of objective information on products in an hierarchical Bayesian modeling framework. Our empirical results show that WOM senders' information choice behavior differs according to the types of information sources. The effects of information sources on WOM activities differ according to the types of WOM messages (subjective evaluation (positive or negative) and objective information). Therefore, our study concludes that WOM activities can be partially managed with effective communication plans influencing on consumers' WOM message choice behavior. The empirical results provide some guidelines for consumers' propagation of information on products companies want.