• Journal of Digital Convergence
• /
• v.14 no.8
• /
• pp.497-502
• /
• 2016

The survey is designed to provide fundamental data for assessing effects of calligraphy therapy program. An opened questionnaire asking psychological and physical experiences (3 advantages and 3 disadvantages) was given to 150 persons practicing calligraphy. Collected data were categorized into 10 psychological advantages (435 items), 6 psychological disadvantages (129 items), 9 physical advantages (302 items), and 7 physical disadvantages (150 items). Those subjective experiences were multidisciplinarily interpreted in terms of the mental and physical health and the humanistic education. A new structured assessing tool which will be developed based on the findings from the study may contribute in activating the calligraphy therapy program.

• Korean Journal of Social Welfare
• /
• v.62 no.4
• /
• pp.223-248
• /
• 2010

This study is to explore the contents and interaction of residents voluntary network and propose the strategies to promote residents voluntary network. The grounded theory was utilized to attain our object. Total of seven social worker and 17 residents participated in the study. Data were collected through in-depth interviews and documents. The data were analyzed by using Strauss and Corbin's method. Results are the followings. In open coding 13 categories, 32 subcategories and 133 concepts were constructed. In axial coding causal conditions were qualitative ascent of needs, emergence of the right welfare consumer. Phenomenon was agitation of praxis ground and grope of exist. Contextual conditions were crisis resources, skepticism of welfare. Intervention conditions were maturation of welfare cognition and proliferation of the sense of community responsibility. Strategy were resocialization of voluntary organization and construction of field related service delivery system. Consequence were grass routing welfare strategic fitting service system. In selective coding we constructed the core category: The praxis revolution from bottom for break social welfare environment.

• The Korean Journal of Applied Statistics
• /
• v.30 no.5
• /
• pp.615-632
• /
• 2017

Unlike randomized trial, statistical strategies for inferring the unbiased causal relationship are required in the observational studies. The matching with the propensity score is one of the most popular methods to control the confounders in order to evaluate the effect of the treatment on the outcome variable. Recently, new methods for the causal inference in latent class analysis (LCA) have been proposed to estimate the average causal effect (ACE) of the treatment on the latent discrete variable. They have focused on the application study for the real dataset to estimate the ACE in LCA. In practice, however, the true values of the ACE are not known, and it is difficult to evaluate the performance of the estimated the ACE. In this study, we propose a method to generate a synthetic data using the propensity score in the framework of LCA, where treatment and outcome variables are latent. We then propose a new method for estimating the ACE in LCA and evaluate its performance via simulation studies. Furthermore we present an empirical analysis based on data form the 'National Longitudinal Study of Adolescents Health,' where puberty as a latent treatment and substance use as a latent outcome variable.

• Economic and Environmental Geology
• /
• v.38 no.1
• /
• pp.45-55
• /
• 2005

Traditional GIS-based probabilistic spatial data integration models for landslide susceptibility analysis have failed to provide the theoretical backgrounds and effective methods for integration of different types of spatial data such as categorical and continuous data. This paper applies two spatial data integration models including non-parametric empirical estimation and parametric predictive discriminant analysis models that can directly use the original continuous data within a likelihood ratio framework. Similarity rates and a prediction rate curve are computed to quantitatively compare those two models. To illustrate the proposed models, two case studies from the Jangheung and Boeun areas were carried out and analyzed. As a result of the Jangheung case study, two models showed similar prediction capabilities. On the other hand, in the Boeun area, the parametric predictive discriminant analysis model showed the better prediction capability than that from the non-parametric empirical estimation model. In conclusion, the proposed models could effectively integrate the continuous data for landslide susceptibility analysis and more case studies should be carried out to support the results from the case studies, since each model has a distinctive feature in continuous data representation.

• The Korean Journal of Applied Statistics
• /
• v.27 no.7
• /
• pp.1077-1095
• /
• 2014

Unlike randomized trial, statistical strategies for inferring the unbiased causal relationship are required in the observational studies. Recently, new methods for the causal inference in the observational studies have been proposed such as the matching with the propensity score or the inverse probability treatment weighting. They have focused on how to control the confounders and how to evaluate the effect of the treatment on the result variable. However, these conventional methods are valid only when the treatment variable is categorical and both of the treatment and the result variables are directly observable. Research on the causal inference can be challenging in part because it may not be possible to directly observe the treatment and/or the result variable. To address this difficulty, we propose a method for estimating the average causal effect when both of the treatment and the result variables are latent. The latent class analysis has been applied to calculate the propensity score for the latent treatment variable in order to estimate the causal effect on the latent result variable. In this work, we investigate the causal effect of adolescents delinquency on their substance use using data from the 'National Longitudinal Study of Adolescent Health'.

• Journal of Animal Science and Technology
• /
• v.48 no.3
• /
• pp.337-344
• /
• 2006

The objective of this study was to compare of genetic parameter estimates on carcass traits of Hanwoo(Korean Cattle) according to modeling with Gibbs sampler and MTDFREML. The data set consisted of 1,941 cattle records with 23,058 animals in pedigree files at Hanwoo Improvement Center. The variance and covariance among carcass traits were estimated via Gibbs sampler and MTDFREML algorithms. The carcass traits considered in this study were longissimus dorsi area, backfat thickness, and marbling score. Genetic parameter estimates using Gibbs sampler and MTDFREML from single-trait analysis were similar with those from multiple-trait analysis. The estimated heritabilities using Gibbs sampler were .52～.54, .54 ～.59, and .42～.44 for carcass traits. The estimated heritabilities using MTDFREML were .41, .52～.53, and .31～.32 for carcass traits. The estimated genetic correlation using Gibbs sampler and MTDFREML of LDA between BF and MS were negatively correlated as .34～.36, .23～.37. Otherwise, genetic correlation between BF and MS was positive genetic correlation as .36～.44. The correlations of breeding value for marbling score between via MTDFREML and via Gibbs sampler were 0.989, 0.996 and 0.985 for LDA, BF and MS respectively.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.2
• /
• pp.524-531
• /
• 2017

Summary The purpose of this study was to understand the tendency and the meaning of day care center teachers regarding role playing through metaphorical analysis. The data were collected from 166 day care center teachers who participated in A-city university supplement education using the sentence completion metaphorical method. The collected data were categorized and analyzed through a qualitative research method conducted by 2 early childhood education specialists. The results are as follows. First, the tendency of role playing metaphorical expression was divided into 3 categories, 8 contents and the frequency of 'sociality development' was the highest followed by 'emotional development', 'development'. Second, the meaning of role playing metaphorical expression was recognized as 'social skills', 'role experience', 'imitation', and 'understanding of society' in the 'sociality development' category; as 'imagination', 'purification function', and 'means of expression' in the 'emotional development' category; and as 'essential factor of development' in the 'development' category. Based on the research result, it was suggested that the roles of education and teachers for the value and effective operation of role playing in early childhood education institutes should be reconsidered.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2000.10a
• /
• pp.555-558
• /
• 2000

소프트웨어 프로세스 능력 수준에 영향을 미치는 요인을 찾아내어, 강점은 격려하고 약점을 개선하는 프로세스 개선활동은 기업의 경쟁력 향상을 위하여 매우 중요한 일이다. 본 연구에서는 이러한 요인을 찾아내기 위하여 SPICE(ISO/IEC 15504) 프로젝트에서 국제적으로 실시된 소프트웨어 심사 결과를 이용하였다. 분석 요인으로 IT부서 사원수, ISO 9001 인증여부, 안정성, 경제적 손실도, 보안성, 환경 영향도를 사용하였으며, 본 자료가 범주형이므로 분석 방법으로 통계적인 방법론인 "수량화방법 II"를 이용하였다. 수량화방법 II에서는 요인의 중요도를 나타내는 지표로 범위와 편상관을 사용한다. "범위"를 지표로 할 경우, 보안성이 능력수준과 가장 높은 관련이 있는 것으로 나타났으며, "편상관"을 지표로 할 경우, ISO 9001 인증이 가장 관련이 높은 것으로 나타났다. 이는 보안성이 높게 요구되는 회사의 경우, 품질시스템이 잘 갖춰져 있고, ISO 9001 인증을 받는 둥의 품질관리를 하여 프로세스 능력수준 또한 높게 나왔다고 추론할 수 있다.

• The Korean Journal of Applied Statistics
• /
• v.35 no.2
• /
• pp.177-188
• /
• 2022

The support vector machine (SVM) has been successfully applied to various classification areas with a high level of classification accuracy. However, it is infeasible to use the SVM in analyzing massive data because of its significant computational problems. When analyzing imbalanced data with different class sizes, furthermore, the classification accuracy of SVM in minority class may drop significantly because its classifier could be biased toward the majority class. To overcome such a problem, we propose the DOC-SVM method, which uses divide-oversampling and conquers techniques. The proposed DOC-SVM divides the majority class into a few subsets and applies an oversampling technique to the minority class in order to produce the balanced subsets. And then the DOC-SVM obtains the final classifier by aggregating all SVM classifiers obtained from the balanced subsets. Simulation studies are presented to demonstrate the satisfactory performance of the proposed method.

• The Korean Journal of Applied Statistics
• /
• v.18 no.2
• /
• pp.471-485
• /
• 2005

For categorical data analysis, the collapsibility were explained with the odds ratio (cross-product ratio). When these theories with these odds ratios are applied to real $2{\times}2{\times}K$ contingency tables, it is impossible to decide whether data are collapsible. Among graphical methods to represent odds ratios, Contour plot which is developed by Doi, Nakamura and Yamamoto (2001) could explain the structure of these data, but cannot decide on the collapsibility. In this paper, by using the Raindrop plot proposed by Barrowman and Myers (2003), we suggest an alternative method which can not only explain the structure of data, but also decide on the collapsibility.