• Journal of the Korean Data and Information Science Society
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• 제17권4호
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• pp.1067-1076
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• 2006

Although the proportional hazards model is the most common approach used for studying the relationship of event times and covariates, alternative models are needed for occasions when it does not fit data. In the two-sample case, proportional odds models are useful for fitting data whose hazard rates converge asymptotically. In this thesis, we propose a new estimator of the relative odds ratio of the proportional odds model when two independent random samples are observed under uncensorship. We prove the asymptotic normality and consistency of the estimator by using martingale-representation. The efficiency of the proposed is assessed through a simulation study.

• Journal of the Korean Data and Information Science Society
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• 제16권4호
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• pp.889-898
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• 2005

In this paper we propose a new estimator of relative odds ratio in the two-sample case of proportional odds model under censorship. Also, we show that the estimator consistent and asymptotically normal by using martingale-representation. The efficiency of the proposed is assessed through a simulation study.

• Journal of the Korean Data and Information Science Society
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• 제16권2호
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• pp.327-334
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• 2005

In this paper we propose a new estimator of relative odds ratio in the two-sample case of proportional odds model. Also, we show that the estimator is consistent and asymptotically normal. The efficiency of the proposed is assessed through a simulation study.

• 치위생과학회지
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• 제8권3호
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• pp.169-173
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• 2008

본 연구는 2007년 3월10일부터 2007년 6월3일까지 충남 당진에 위치한 S대학 치위생과 3학년들의 치면세마 실습환자 248명을 대상으로 치간칫솔 사용에 따른 치면세균막 제거효과를 비례오즈모형(proportional odds models)을 사용하여 분석한 결과 다음과 같은 결론을 얻었다. 1. 비례오즈모형의 적합도는 자유도가 3인 1.2552이고 p값이 .7398로 비례오즈모형이 적절함을 의미하고 치면세균막 제거효과와 치간칫솔 사용의 독립성문제는 $H_0:{\beta}=0$에 대한 검정으로 검정통계량은 자유도가 1인 15.5496이고 p 값은 <.0001 이다. 이는 치면세균막 제거 효과와 치간칫솔의 사용은 매우 연관성이 높음을 의미한다. 2. 모형의$\beta$에 대한 ML추정치는 $\hat{\beta}=1.2493$(ASE = 0.3207)임을 알 수 있고 반응이 매우 불량이다 보다는 매우 양호하다 에 속할(이를 라 표현할 수 있다) 경향은 치간칫솔을 사용하지 않는다. 라는 반응에 비해 치간칫솔을 사 용한다. 라는 경향이 추정오즈비 exp(1.2493) = 3.49배 높다. 3. 비례오즈모형의 추정반응은 치간칫솔을 사용한다. 라는 반응이 매우양호와 양호한 치면세균막 제거효과에 속할 추정(누적)확률은 0.38(0.50)이다.

• 운동영양학회지
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• 제25권1호
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• pp.30-34
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• 2021

[Purpose] Many studies have observed a high prevalence of erectile dysfunction among individuals performing physical activity in less leisure-time. However, this relationship in patients with type 2 diabetic patients is not well studied. In exposure outcome studies with ordinal outcome variables, investigators often try to make the outcome variable dichotomous and lose information by collapsing categories. Several statistical models have been developed to make full use of all information in ordinal response data, but they have not been widely used in public health research. In this paper, we discuss the application of two statistical models to determine the association of physical inactivity with erectile dysfunction among patients with type 2 diabetes. [Methods] A total of 204 married men aged 20-60 years with a diagnosis of type 2 diabetes at the outpatient unit of the Department of Endocrinology at PSG hospitals during the months of May and June 2019 were studied. We examined the association between physical inactivity and erectile dysfunction using proportional odds ordinal logistic regression models and continuation ratio models. [Results] The proportional odds model revealed that patients with diabetes who perform leisure time physical activity for over 40 minutes per day have reduced odds of erectile dysfunction (odds ratio=0.38) across the severity categories of erectile dysfunction after adjusting for age and duration of diabetes. [Conclusion] The present study suggests that physical inactivity has a negative impact on erectile function. We observed that the simple logistic regression model had only 75% efficiency compared to the proportional odds model used here; hence, more valid estimates were obtained here.

• 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.

• Journal of the Korean Data and Information Science Society
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• 제24권6호
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• pp.1465-1475
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• 2013

The chi-square type test statistic is the most commonly used test in terms of measuring testing goodness-of-fit for multinomial logistic regression model, which has its grouped data (binomial data) and ungrouped (binary) data classified by a covariate pattern. Chi-square type statistic is not a satisfactory gauge, however, because the ungrouped Pearson chi-square statistic does not adhere well to the chi-square statistic and the ungrouped Pearson chi-square statistic is also not a satisfactory form of measurement in itself. Currently, goodness-of-fit in the ordinal setting is often assessed using the Pearson chi-square statistic and deviance tests. These tests involve creating a contingency table in which rows consist of all possible cross-classifications of the model covariates, and columns consist of the levels of the ordinal response. I examined goodness-of-fit tests for a proportional odds logistic regression model-the most commonly used regression model for an ordinal response variable. Using a simulation study, I investigated the distribution and power properties of this test and compared these with those of three other goodness-of-fit tests. The new test had lower power than the existing tests; however, it was able to detect a greater number of the different types of lack of fit considered in this study. I illustrated the ability of the tests to detect lack of fit using a study of aftercare decisions for psychiatrically hospitalized adolescents.

• Communications for Statistical Applications and Methods
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• 제7권3호
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• pp.711-720
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• 2000

A case study of modeling ordinal categorical response data with the MARS method is done. The study is to analyze the effect of some personal characteristics and socioeconomic status on the teenage marijuana use. The MARS method gave a new insight into the data set.

• Journal of the Korean Data and Information Science Society
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• 제27권4호
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• pp.1117-1117
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• 2016

Journal of the Korean Data & Information Science Society, Vol. 24, No. 6, 1465-1475, 2013 (http://dx.doi.org/10.7465/jkdi.2013.24.6.1465). This article has been retracted at the research ethics committee.

• 응용통계연구
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• 제29권7호
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• pp.1231-1246
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• 2016

경쟁위험에 대한 연구 중 주로 쓰이는 방법은 Cause-specific 위험 모형과 subdistribution을 이용한 비례 위험 모형 방법이다. 그 이후에도 많은 모형이 제시되었지만, 추정 방법 면에서 설명력이 부족하거나 알고리즘으로 구현하기 어려운 단점을 가지고 있어서 잘 활용되고 있지 않다. 이 논문에서는 Cause-specific 위험 모형, subdistribution을 이용한 비례 위험 모형과 비교적 최근에 제시된 이항 회귀 모형(direct binomial model), 절대 위험 회귀 모형(absolute risk regression model), Eriksson 등 (2015)의 비례 오즈 모형(proportional odds model)을 소개하고 추정 방법을 간단히 설명하고자 한다. 각 모형에 대하여 SAS와 R을 이용한 활용 방법을 제시하고, 두 가지 경쟁위험이 존재하는 데이터를 R을 이용하여 분석하였다.