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

• Korea journal of population studies
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• v.30 no.1
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• pp.49-66
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• 2007

본 연구는 2001년 한국에서 사망한 60세 이상 노인들 62,000명의 사망기록 자료를 이용하여 사망원인의 다양성을 보여주는 한편 치매에 의한 사망원인을 가장 잘 예측할 수 있는 변수를 경험적으로 규명하고자 실시하였다. 이와 같은 목적을 위한 연구내용은 다음과 같다. 첫째, 노인들의 주요 사망원인에 해당하는 악성종양, 뇌혈관 질환, 심장병, 당뇨, 만성 호흡기 질환, 치매, 고혈압, 간 질환, 사고, 결핵 및 기타 질병 등 11개 사망원인에 대하여 빈도분석을 실시하였다. 둘째, 60세 이상 사망자들 가운데 치매에 의한 사망원인과 나머지 19개의 사망원인을 비교하여 치매에 의한 사망에 영향을 미치는 요인들을 다항로지스틱회귀분석을 통해 분석하였다. 그 결과, 한국의 노인인구 가운데 연령이 높을수록 치매로 인하여 사망할 가능성(우도비)이 높으며 여성이 남성에 비해 치매에 의하여 사망할 가능성이 높은 것으로 밝혀졌다. 그러나 교육수준이 높을수록 치매에 의하여 사망할 가능성이 낮은 것으로 나타났으며 거주지역은 치매에 의한 사망과 통계적으로 유의미한 관계가 있었으나 일관성은 없는 것으로 밝혀졌다. 한편 결혼지위는 치매에 의한 사망과 통계적으로 유의미한 관계가 없는 것으로 나타났다.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.354-354
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• 2021

2020년은 장마기간이 49일간 지속됨에 따라 침수, 산사태 등 많은 홍수피해가 발생하였다. 특히 서울에서는 한강 본류의 수위가 급격하게 증가함에 따라 둔치 및 도로 침수 피해가 발생하였다. 이처럼 하천의 수위증가로 인한 홍수피해에 대응하기 위해 홍수통제소 및 기초지자체에서는 홍수특보를 발령한다. 이 홍수특보는 수위관측소 지점별 계획홍수량의 50 %, 70 % 이상의 홍수량이 발생할 경우 홍수주의보와 홍수경보가 발령되며, 이 기준은 각 권역별로 동일하다. 하지만 2017년 의정부시에서는 중랑천 수위증가로 인해 주변 지역에 침수피해가 발생하였지만, 이때 홍수량은 계획홍수량 대비 약 30 %에 불과하였다. 이처럼 한강권역 내 하천수위 증가로 인한 홍수피해는 계획홍수량의 50 % 이내에서 발생하기도 한다. 이에 본 연구에서는 한강권역을 대상으로 현재 2단계로 발령되는 홍수특보를 3단계로 세분화하고자 하였다. 단계별 홍수량 위험기준을 산정하기 위해 과거 홍수피해 발생 이력이 있는 한강권역 내 43개의 수위관측소 지점을 선정하였으며, 지점별 홍수기 동안의 홍수량 및 피해액 자료를 수집하였다. 각 단계별 홍수량 기준을 산정하기 위해서는 로지스틱 회귀분석 방법을 활용하여 피해발생 확률을 산정하였다. 1단계 기준은 계획홍수량 대비 홍수량 비율과 홍수피해 발생여부를 고려한 이항 로지스틱 회귀분석 모델을 구축한 후 3계 도함수에 적용하여 홍수피해 발생확률이 급격하게 증가하는 특이점을 산정하였다. 2단계와 3단계 기준은 다항 로지스틱 회귀분석 중 계층형 로지스틱 회귀분석을 활용하여 지점별 피해액 비율이 60 ~ 80 %, 80 ~ 100 % 구간에 속할 확률을 산정하고, 1단계와 동일한 방법으로 특이점을 산정하였다. 그 결과 지점별로 기존 제공되고 있는 홍수특보 기준을 과거 발생한 홍수피해를 고려하여 세분화할 수 있었으며, 이 결과는 지역별 홍수피해 저감대책에 활용될 수 있을 것으로 판단된다.

• The Korean Journal of Applied Statistics
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• v.23 no.5
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• pp.857-870
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• 2010

This study was conducted to investigate the relationship between the socio-demographic factors and the Korean consumers palatability evaluation grades with Hanwoo sensory evaluation data from 2006 to 2008 by National Institute of Animal Science. The dichotomy logistic regression model and the multinomial logistic regression model are fitted with the independent variables such as the consumer living location, age, gender occupation, monthly income, beef cut and the the palatability grade as the categorical dependent variable and tenderness, 리avor and juiciness as the continuous dependent variable. Stepwise variable selection procedure is incorporated to find the final model and odds ratios are calculated to nd the associations between categories.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.177-179
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• 2023

본 연구에서는 사회복지시설 종사사의 직무만족도 유형을 살펴보고 유형별 예측변인과의 영향관계를 검증하였다. 이러한 연구목적을 검증하기 위해 보건복지부의 '사회복지시설 실태조사'(2014년) 데이터에서 직무만족도 변인에 모두 응답한 11,660명을 최종 분석하였다. 잠재프로파일 분석결과, 사회복지사의 직무만족도 유형은 4집단으로 나타나 '최상 직무만족도집단', '중상 직무만족도집단', '중간 직무만족도집단', '최하 직무만족도집단'으로 명명하였다. 다항로지스틱 분석결과, CLASS4(최상 직무만족도집단)를 준거집단으로 하여 CLASS1(최하 직무만족도집단)과 비교해 노동강도대비 보수수준 평가, 타직종대비 보수수준 평가, 시설안전도, 인권보장도를 높게 인식할수록 CLASS4(최상 직무만족도집단)에 속할 확률이 높아지는 것으로 나타났다. 다만, 이직의사는 낮을수록 CLASS4(최상 직무만족도집단)에 속할 확률이 높아지는 것으로 나타났다. CLASS4를 준거집단으로 하여 CLASS2집단, CLASS3집단도 비교분석 하였다.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.148-163
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• 2021

The diversification of the New Deal urban regeneration projects, that started in 2017 in accordance with the "Special Act on Urban Regeneration Activation and Support", generated the increased demand for the accuracy of data-driven diagnosis and project type forecast. Thus, this research was conducted to develop an application model able to identify the most appropriate New Deal project type for "eup", "myeon" and "dong" across the country. Data for application model development were collected through Statistical geographic information service(SGIS) and the 'Urban Regeneration Comprehensive Information Open System' of the Urban Regeneration Information System, and data for the analysis model was constructed through data pre-processing. Four models were derived and simulations were performed through polynomial regression analysis and multinomial logistic regression analysis for the application of the appropriate New Deal project type. I verified the applicability and validity of the four models by the comparative analysis of spatial distribution of the previously selected New Deal projects by targeting the sites located in Seoul by each model and the result showed that the DI-54 model had the highest concordance rate.

• The Journal of Engineering Geology
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• v.31 no.1
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• pp.31-42
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• 2021

Database of Cut-slope management system (CSMS) has been constructed based on investigations of all slopes on the roads of the whole country. The investigation data is documented by human, so it is inevitable to avoid human-error such as missing-data and incorrect entering data into computer. The goal of this paper is constructing a prediction model based on several machine-learning algorithms to solve those imperfection problems of the CSMS data. First of all, the character-type data in CSMS data must be transformed to numeric data. After then, two algorithms, i.g., multinomial logistic regression and deep-neural-network (DNN), are performed, and those prediction models from two algorithms are compared. Finally, it is identified that the accuracy of DNN-model is better than logistic model, and the DNN-model will be utilized to improve data-quality.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.2
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• pp.404-414
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• 2020

This study aims to explore latent classes in terms of changing patterns in achievement motivation among the samples from elementary school to middle school students in multicultural families and to investigate factors to predict latent groups and their relationship with academic achievement. 1254 pairs of mother and child from the 1st to 6th years of Multicultural Adolescents Panel Study (MAPS) was utilized for the Latent Class Growth Analysis (LCGA), One-way ANOVA, Multinomial Logistic Regression. The results showed that there were four distinct subgroups within the samples in terms of achievement goal orientations (i.e. very-high changing group, average changing group, low stable group, very-low stable group) at all six time points, and students who reported high achievement motivation were likely to have higher academic achievement. Four groups were extracted based on parent's efficacy, students' self-esteem, and teacher's support. Suggestions and practical implications for understanding the types of subgroups for the achievement motivation of multicultural families were discussed.

• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.1021-1026
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• 2017

Mixture experiments are commonly encountered in many fields including food, chemical and pharmaceutical industries. In mixture experiments, measured response depends on the proportions of the components present in the mixture and not on the amount of the mixture. Statistical analysis of the data from mixture experiments has mainly focused on a continuous response variable. In the example of quantal response data in mixture experiments, however, the tumor incidence data have been analyzed in Chen et al. (1996) to study the effects of 3 dietary components on the expression of mammary gland tumor. In this paper, we compared the logistic regression models with linear predictors such as second degree Scheffe polynomial model, Becker model and Akay model in terms of classification accuracy.

• The Journal of the Korea Contents Association
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• v.22 no.6
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• pp.530-540
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• 2022

The aim of this study was to analyze the impacts of perceived economic instability on drinking frequency in the mist of exercising the strong social distancing in the early phase of COVID19 pandemic. The data were collected from 1,117 adults aged between 19 and 70 across the nation from May 13 to May 19 in 2020 by Embrain, an on-line research company. We used only 820(73.4%) out of 1,117 who answered that they had a drinking in 2020. Bi-variate analysis and multivariate multinomial logistic regression were performed using STATA16. Multinomial logistic regression results showed that the increase of employment instability was related to the increase of drinking frequency, whereas the increase of income instability was related to the decrease of drinking frequency. In sum, the impact of perceived economic instability during the early phase of pandemic may be presented as an increase or decrease of drinking frequency depending on the effect of employment instability and income instability.