The purpose of this study is to investigate the influence of social factors on the use of honorific language by discourse completion test. Participants complete a short discourse by filling in their responses in conversations that may occur in families, schools, and workplaces where the social status and solidarity of the listener is predetermined. Honorific styles of sentence endings of their responses are analyzed by the generalized linear mixed model. The results show that social status and solidarity are statistically significant factors in the use of honorific styles, but their effects are dependent on the discourse situation. The ratio of using honorific styles gradually increases as the formality of situation increases (i.e., family < school < workplace). Interestingly, when the solidarity is low at the workplace, the ratio of using honorific styles is consistently high regardless of the social status of the listener. These results show that the use of Korean honorific styles is pragmatically changing according to the discourse situation.

This study proposes the generation mechanism of various design matrix using generalized linear model for design of experiment. Design generation method of GLM analysis, factorial design(FD) with center points, ANOVA design with lack-of-fit test, and response surface design are introduced. In central composite(CC) design, orthogonal blocking and fractional factorial design(FFD) are presented. We compare the design of Box-Benhken(BB) and face-centred central compsite design.

The purpose of this study is to analyze the determinants of the digital divide at individual level and regional level in Korea, considering interaction between individual and the regional variables. Following results are obtained. First, individual level digital devide in the 16 different regions has been found in terms of Internet use, implying the needs for further analysis on impact of the regional factor in individual Internet use. Second, the result finds the impact of level-l individual variables, "gender, age, education, income and jobs" on digital divide, significantly at level 10% level. Third, the regional variables influencing the individual digital divide were not found at state level. However, regional factors might affect digital devide at county level. Study suggest some plans to reduce digital divide. First, the digital devide at individual level should be remedied by focusing on neglected class of people. Second, we need to approach the digital divide by analyzing in more detail, reflecting interactions of the regional variables and individual variables. Third, we should come up with a policy for mending the digital divide at regional level.