• 응용통계연구
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• 제23권6호
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• pp.1057-1065
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• 2010

In this paper we discuss some cautionary notes in using the Pearson chi-squared test statistic for the goodness-of-fit of the ordinal response model. If a model includes continuous type explanatory variables, the resulting table from the t of a model is not a regular one in the sense that the cell boundaries are not fixed but randomly determined by some other criteria. The chi-squared statistic from this kind of table does not have a limiting chi-square distribution in general and we need to be very cautious of the use of a chi-squared type goodness-of-t test. We also study the limiting distribution of the chi-squared type statistic for testing the goodness-of-t of cumulative logit models with ordinal responses. The regularity conditions necessary to the limiting distribution will be reformulated in the framework of the cumulative logit model by modifying those of Moore and Spruill (1975). Due to the complex limiting distribution, a parametric bootstrap testing procedure is a good alternative and we explained the suggested method through a practical example of an ordinal response dataset.

• Journal of the Korean Data and Information Science Society
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• 제18권2호
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• pp.471-479
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• 2007

This paper discusses about how to build up mixed-effects model for analysing ordinal response data by using cumulative logits. Random factors are assumed to be coming from the designed sampling scheme for choosing observational units. Since the observed responses of individuals are ordinal, a proportional odds model with two random effects is suggested. Estimation procedure for the unknown parameters in a suggested model is also discussed by an illustrated example.

• Communications for Statistical Applications and Methods
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• 제16권4호
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• pp.697-705
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• 2009

The Pearson chi-squared statistic or the deviance statistic is widely used in assessing the goodness-of-fit of the generalized linear models. But these statistics are not proper in the situation of continuous explanatory variables which results in the sparseness of cell frequencies. We propose a goodness-of-fit test statistic for the cumulative logit models with ordinal responses. We consider the grouping of a dataset based on the ordinal scores obtained by fitting the assumed model. We propose the Pearson chi-squared type test statistic, which is obtained from the cross-classified table formed by the subgroups of ordinal scores and the response categories. Because the limiting distribution of the chi-squared type statistic is intractable we suggest the parametric bootstrap testing procedure to approximate the distribution of the proposed test statistic.

• Communications for Statistical Applications and Methods
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• 제24권1호
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• pp.81-96
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• 2017

Cumulative logit random effects models are typically used to analyze longitudinal ordinal data. The random effects covariance matrix is used in the models to demonstrate both subject-specific and time variations. The covariance matrix may also be homogeneous; however, the structure of the covariance matrix is assumed to be homoscedastic and restricted because the matrix is high-dimensional and should be positive definite. To satisfy these restrictions two Cholesky decomposition methods were proposed in linear (mixed) models for the random effects precision matrix and the random effects covariance matrix, respectively: modified Cholesky and moving average Cholesky decompositions. In this paper, we use these two methods to model the random effects precision matrix and the random effects covariance matrix in cumulative logit random effects models for longitudinal ordinal data. The methods are illustrated by a lung cancer data set.

• 수산해양교육연구
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• 제27권6호
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• pp.1693-1703
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• 2015

This study is aimed to retain objectivity and generality against consumer perception about seafood of Hebei Spirit oil spill incident area, and analyze gap of consumer perception in according to confidence level of seafood using ordinal logit model. As results, This article have three implications. First, Consumer don't have high confidence level in comparison with previous research. Second, It is important to retain confidence of quality for purchasing seafood of oil spill incident area. Third, Consumer perception is improved positively against seafood of oil spill area. But This study has limits that don't take regional opinion and situation into account.

• The Journal of Asian Finance, Economics and Business
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• 제9권6호
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• pp.69-79
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• 2022

The purpose of the study is to look into the likelihood of private sector enterprises going bankrupt due to COVID-19 pandemic-related issues. The data for this study was taken from the World Bank's Enterprise Survey, which was intended to assess the impact of the COVID-19 pandemic on the business sector. This study uses the Ordinal Logit Method to analyze the model with dependent variables having ordinal values. The determinants reflect business performance, innovation, business relationships, and government support. According to the estimation results, a lower probability of business closures, illiquidity, and payment delays are found in businesses that maintain sales growth, operating hours, temporary workers, product portfolio, consumer demand, and input supply. Meanwhile, the increase in online business activities and receiving support from financial institutions and the government do not help businesses reduce the risk. Moreover, higher survival is found in manufacturing and developing countries. This implies the fragility of businesses in the retail and service sectors, especially for mega-enterprises in developed countries. In addition, the negative impact of the COVID-19 pandemic on businesses in Europe and West Asia is less severe than in other regions. The results imply policies to support the private sector during the pandemic, such as increasing labor market flexibility or rapidly implementing supportive policies.

• 대한토목학회논문집
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• 제32권3D호
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• pp.275-281
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• 2012

본 연구는 동기와 방문의 관련성을 해안형과 도심형으로 장소 유형을 분류하여 부산지역 특정 장소를 방문하는 방문객을 대상으로 조사하여 그들 사이의 관계를 조사하고자 하는 것이다. 방문객들은 방문지를 선택하는 데 있어 다양한 목적과 동기를 가지고 참여하게 되며 일반적으로, 방문 동기는 방문객들의 방문 행동을 이해하거나 방문지 선택과정에 중요한 개념으로 받아들여지고 있다. 방문객들이 왜 특정 장소를 선택하여 방문하는지를 이해하는 것은 방문 대상지의 정책 수립이나 마케팅에도 강력한 도구 역할을 하기 때문에 연구의 필요성이 제기된다. 따라서 본 연구에서는 직접 설문을 통하여 이러한 동기와 방문의 관련성을 부산지역 특정 장소를 방문하는 방문객을 대상으로 조사하여 그들 사이의 관계를 조사하였다. 장소의 방문 동기별 방문의 관련성을 방문객을 대상으로 조사하여 관계를 직접적으로 조사 분석함으로써, 만족도 수준에 영향을 줄 수 있는 특정한 속성 및 서비스의 집중과 대상지의 마케팅 계획수립의 방향을 제시하는 의미 있는 근거를 Ordinal Logit Model을 이용하여 제시하는데 그 목적이 있다.

• 응용통계연구
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• 제10권1호
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• pp.151-161
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• 1997

순서적 다항자료의 누적로짓 모형에 대한 베이지안 사후추론을 위하여 몬테칼로 깁스표본기법을 제안하였다. 원래의 모형에서는 깁스표본기법 적용에 필수적으로 요구되는 각 원소모수의 조건부 확률분포가 난수생성에 편리한 형태로 주어지지 않으므로 Albert and Chib(1993)과 Oh(1997)에서 이항 로짓모형에 사용한 바와 같이 적절한 잠재변수를 도입하여 깁스표본기법 적용에 매우 편리한 형태를 갖도록 한다.

• 대한토목학회논문집
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• 제29권2D호
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• pp.287-293
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• 2009

본 연구는 재개발 이후 원주민들의 재정착 비용 및 재정착 결정요인을 분석하고자 하는 것이다. 재정착비용의 범위는 실 데이터를 활용하여 재개발 후 해당지역의 기존아파트 시세의 평균증가율이 204%를 나타남을 보였다. 이에 근거하여 재정착비용을 원주민 종전자산가격의 150% 이하, 180% 이하, 200% 이하 그리고 200% 초과의 4개의 구간으로 설정하여 설문을 실시하였다. 분석대상 지역으로 부산시 재정비촉진지구로 지정된 4개의 지역인 서금사재정비촉진지구, 시민공원재정비촉진지구, 충무재정비촉진지구 그리도 영도재정비촉진지구 지역을 대상으로 설문조사를 실시하였다. 독립변수는 크게 가구주특성, 주거생활특성, 주택특성 그리고 재정비에 관한 원주민의 견해로 구성하였다. 분석방법으로는 순서화된 재정착의 비용범위 중 하나의 구간을 선택한 응답자와 그 외의 구간을 선택한 응답자간의 특성을 파악할 수 있는 순서형로짓모형(Ordinal Logit Model)을 이용하여 분석하였다. 분석결과는 다음과 같다. 원주민이 생각하는 재정착비용의 범위는 원주민 종전자산가격의 1.5배정도 상승한 가격이 적당한 것으로 나타났으며, 유의한 변수로는 가구주 특성에서 성별, 직업, 소득 주거생활특성에서는 주거지역만족도, 지역애착도 주택특성으로는 주택형태, 주택규모, 소유형태 마지막으로 재정비에 관한 원주민의 견해에서는 완료기간으로 나타났다.

• 산업공학
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• 제15권2호
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• pp.209-217
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• 2002

Quality of Service(QoS) in the telecommunications can be evaluated by analyzing the opinion data which result from the surveyed opinions of respondents and quantify subjective satisfaction on the QoS from the customers' viewpoints. For analyzing the opinion data, MOS(mean opinion score) method and Cumulative Probability Curve method are often used. The methods are based on the scoring method, and therefore, have the intrinsic deficiency due to the assignment of arbitrary scores. In this paper, we propose an analysis method of the opinion data using logit models which can be used to analyze the ordinal categorical data without assigning arbitrary scores to customers' opinion, and develop an analysis procedure considering the usage of procedures provided by SAS(Statistical Analysis System) statistical package. By the proposed method, we can estimate the relationship between customer satisfaction and network performance parameters, and provide guidelines for network planning. In addition, the proposed method is compared with Cumulative Probability Curve method with respect to prediction errors.