• The Korean Journal of Applied Statistics
• /
• v.33 no.1
• /
• pp.25-46
• /
• 2020

This paper presents ordinal probit semiparametric regression models using Bayesian Spectral Analysis Regression (BSAR) method. Ordinal probit regression is a way of modeling ordinal responses - usually more than two categories - by connecting the probability of falling into each category explained by a combination of available covariates using a probit (an inverse function of normal cumulative distribution function) link. The Bayesian probit model facilitates posterior sampling by bringing a latent variable following normal distribution, therefore, the responses are categorized by the cut-off points according to values of latent variables. In this paper, we extend the latent variable approach to a semiparametric model for the Bayesian ordinal probit regression with nonparametric functions using a spectral representation of Gaussian processes based BSAR method. The latent variable is decomposed into a parametric component and a nonparametric component with or without a shape constraint for modeling ordinal responses and predicting outcomes more flexibly. We illustrate the proposed methods with simulation studies in comparison with existing methods and real data analysis applied to a Korean National Health and Nutrition Examination Survey (KNHANES) 2016 for investigating nonparametric relationship between smoking behavior and coffee intake.

• 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.

• 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.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 the Korean Data and Information Science Society
• /
• v.24 no.4
• /
• pp.815-824
• /
• 2013

Traditional Pearson chi-squared test is not appropriate for the data collected by the complex sample design. When one uses the traditional Pearson chi-squared test to the complex sample categorical data, it may give wrong test results, and the error may occur not only due to the biased variance estimators but also due to the biased point estimators of cell proportions. In this study, the design based consistent Wald test statistics was derived for k-population homogeneity test, and the traditional Pearson chi-squared test statistics was partitioned into three parts according to the causes of error; the error due to the bias of variance estimator, the error due to the bias of cell proportion estimator, and the unseparated error due to the both bias of variance estimator and bias of cell proportion estimator. An analysis was conducted for empirical results of the relative size of each error component to the Pearson chi-squared test statistics. The second year data from the fourth Korean national health and nutrition examination survey (KNHANES, IV-2) was used for the analysis. The empirical results show that the relative size of error from the bias of variance estimator was relatively larger than the size of error from the bias of cell proportion estimator, but its degrees were different variable by variable.

• The Korean Journal of Applied Statistics
• /
• v.31 no.6
• /
• pp.721-732
• /
• 2018

Latent class analysis (LCA) is an important tool to explore unseen latent groups in multivariate categorical data. In practice, it is important to select a suitable set of variables because the inclusion of too many variables in the model makes the model complicated and reduces the accuracy of the parameter estimates. Dean and Raftery (Annals of the Institute of Statistical Mathematics, 62, 11-35, 2010) proposed a headlong search algorithm based on Bayesian information criteria values to choose meaningful variables for LCA. In this paper, we propose a new variable selection procedure for LCA by utilizing posterior probabilities obtained from each fitted model. We propose a new statistic to measure the adequacy of LCA and develop a variable selection procedure. The effectiveness of the proposed method is also presented through some numerical studies.

• The Korean Journal of Applied Statistics
• /
• v.12 no.1
• /
• pp.275-293
• /
• 1999

다구찌의 누적법은 다구찌 품질공학에서 중요한 통계분석 방법이다. 그러나 이 방법이 복잡하고 비효율적일 뿐만 아니라 실험의 결과가 잘못 해석 될 수 있는 문제점을 가지고 이싿. 특히 순서 지어진 범주형에 관한 다요인(multificator) 실험에서는 이러한 가능성이 큰 것으로 지적되고 있다. 이에 대한 걱정과 비판이 Nair(1986) 그리고 Hamada and Wu(1990)에 의하여 심각하게 제기되어 왔다. 본 논문은 이러한 내용들을 정리하고 이들의 논란과 주장에 대한 평가와 이에대한 최선의 실천방안을 제안하고 있다. 아울러 실제 자료분석을 위하여 필요한 SAS/IML 프로그램을 제시하고 있다.

• Journal of Korean Elementary Science Education
• /
• v.41 no.1
• /
• pp.44-64
• /
• 2022

This study explored the elementary school teachers' experiences while teaching students with low achievement in science based on the grounded theory. In-depth interviews and analysis were conducted on 13 teachers with experiences in teaching students with low achievement in science within the last three years and more than five years of field experience until the theoretical saturation of data on the teaching experiences for students with low achievement in science. The analysis results were as follows. First, the teaching experiences of elementary school teachers for underachievers in science were classified into 119 concepts, 41 subcategories, and 17 categories. Based on the paradigm model, the categories were structured and presented as causal conditions, contextual conditions, intervening conditions, action/interaction strategies and consequences based on the central phenomenon of 'difficulty in teaching students with low achievement in science'. Second, the core category of elementary school teachers' teaching underachievers in science was assumed to be 'overcoming difficulties and teaching underachievers in science'. And according to the properties and dimensions of the core category, teachers who teaching students with low achievement in science were divided into four types: 'compromising-', 'overcoming-', 'accepting-', and 'conflicting-reality type'. Third, a conditional matrix was presented to summarize and integrate the results of this study by classifying the teaching experience of elementary school teachers for underachievers in science into educational providers and educational demanders. On the basis of these findings, educational implications for teaching students with low achievement in science were discussed.

• Journal of the HCI Society of Korea
• /
• v.12 no.2
• /
• pp.31-40
• /
• 2017

This a qualitative research about the virtual personal assistant, voice recognition device SKT 'NUGU' which was launched on September 1, 2016. For the study, an in-depth interview was committed with the 9 research participants who had used this device for more than a month. For the result of the interview, 362 concepts were discovered and through open coding, axis coding, selective coding the concepts got categorized in 16 sub-categories and 10 top categories. After recognizing 362 concepts from the interview sources, I proposed a paradigm model from the open coding. And from the selective coding, the main category of the study has been narrowed down to understand the 'Usage Patterns by Each Type'. As a result of the typification, it was confirmed that the usage pattern can be described in two different types of the dependent and inquiry type. From the result of the research, it provided the basic data about the user experience of virtual assistant which can be utilized when suggesting virtual personal assistant in the near future.

• The Korean Journal of Applied Statistics
• /
• v.21 no.4
• /
• pp.589-602
• /
• 2008

This article studies on disability pensioners' characteristic with multinomial logit and logistic regression model. Seven factors are examined on whether each factor is reflected in degree of disability in the disability pension. By incorporating multinomial logit and logistic regression model, effectiveness and characteristic of the seven factors are investigated on the degree of disability. Result shows all the seven factors are significant on the degree of disability, while among the seven, five factors, age, sex, type of coverage, type of category, insured duration show a trend in degree of disability and the other two, cause of disability and class of standard monthly income are not effective on trend in degree of disability. Results from analyses might be useful for disability pension management.