• Title/Summary/Keyword: Cox proportional hazard model

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The relative risk of major risk factors of ischemic heart disease (주요 위험요인별 허혈성심질환 사망위험도 분석)

  • Ko, Min-Jung;Han, Jun-Tae
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.2
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    • pp.201-209
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    • 2010
  • Due to the dramatic increase of mortality from ischemic heart disease (IHD) during the last decade, it is highly warranted to present the effective prevention strategy. Therefore this study identified the major risk factors of IHD over 10 years of follow-up among 2,268,018 participants of National Health Insurance Exam in 1996 with Cox proportional hazard model. In men, BMI, blood pressure, smoking were significantly associated with IHD, whereas hypertension, perceived health status and ${\gamma}$-GTP were related with IHD in women.

Analysis of Spatial Characteristics of Business-Type-Changed Parcel in Hongik-University Commercial Area, Seoul - Focused on the View Point of Commercial Gentrification - (서울시 홍대상권 내 업종변화 필지의 공간적 특성 분석 - 상업 젠트리피케이션의 관점에서 -)

  • Kim, Dongjun;Kim, Kijung;Lee, Seungil
    • Journal of Korea Planning Association
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    • v.54 no.2
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    • pp.5-16
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    • 2019
  • The purpose of this study is to analyze the spatial characteristics of business-type-changed parcel in the Hongik-University commercial area, from the view point of commercial gentrification. A commercial gentrification occurs through a business-type-change in a spatial basic unit (microscopic spatial unit such as parcel) of an area which has not been considered in relavent policies and research. So, this study analyzed the spatial characteristics of business-type-changed parcels using the Cox's proportional hazard regression model. The main results of this study are as follows. First, as new developments in the adjacent area occur, the business-type-change probability increases. Second, by the commercial area division, the business-type-change probability is different. Finally, the accessibility is better, the probability is higher. These results could suggest that a consideration of the spatial characteristics form microscopic viewpoint is necessary to understand the commercial gentrification. And these could be used as basic data for a gentrification diagnostic and management system, which can predict gentrification from the view point of business-type-change on the basis of a parcel.

First Job Waiting Times after College Graduation Based on the Graduates Occupational Mobility Survey in Korea

  • Lee, Sungim;Moon, Jeounghoon
    • The Korean Journal of Applied Statistics
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    • v.25 no.6
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    • pp.959-975
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    • 2012
  • Each year research institutions such as the Korea Employment Information Service(KEIS), a government institution established for the advancement of employment support services, and Job Korea, a popular Korean job website, announce first job waiting times after college graduation. This provides useful information understand and resolve youth unemployment problems. However, previous reports deal with the time as a completely observed one and are not appropriate. This paper proposes a new study on first job waiting times after college graduation set to 4 months prior to graduation. In Korea, most college students hunt for jobs before college graduation in addition, the full-fledged job markets also open before graduation. In this case the exact waiting time of college graduates can be right-censored. We apply a Cox proportional hazards model to evaluate the associations between first job waiting times and risk factors. A real example is based on the 2008 Graduates Occupational Mobility Survey(GOMS).

A Study on the Conditional Survival Function with Random Censored Data

  • Lee, Won-Kee;Song, Myung-Unn
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.2
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    • pp.405-411
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    • 2004
  • In the analysis of cancer data, it is important to make inferences of survival function and to assess the effects of covariates. Cox's proportional hazard model(PHM) and Beran's nonparametric method are generally used to estimate the survival function with covariates. We adjusted the incomplete survival time using the Buckley and James's(1979) pseudo random variables, and then proposed the estimator for the conditional survival function. Also, we carried out the simulation studies to compare the performances of the proposed method.

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A Covariate-adjusted Logrank Test for Paired Survival Data

  • Jeong, Gyu-Jin
    • Communications for Statistical Applications and Methods
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    • v.9 no.2
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    • pp.533-542
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    • 2002
  • In this paper, a covariate adjusted logrank test is considered for censored paired data under the Cox proportional hazard model. The proposed score test resembles the adjusted logrank test of Tsiatis, Rosner and Tritchler (1985), which is derived from the partial likelihood. The dependence structure for paired data is accommodated into the test statistic by using' sum of square type' variance estimators. Several weight functions are also considered, which produce a class of covariate adjusted weighted logrank tests. Asymptotic normality of the proposed test is established and simulation studies with moderate sample size show the proposed test works well, particularly when there are dependence structure between treatment and covariates.

Estimating the Mixture of Proportional Hazards Model with the Constant Baseline Hazards Function

  • Kim Jong-woon;Eo Seong-phil
    • Proceedings of the Korean Reliability Society Conference
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    • 2005.06a
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    • pp.265-269
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    • 2005
  • Cox's proportional hazards model (PHM) has been widely applied in the analysis of lifetime data, and it can be characterized by the baseline hazard function and covariates influencing systems' lifetime, where the covariates describe operating environments (e.g. temperature, pressure, humidity). In this article, we consider the constant baseline hazard function and a discrete random variable of a covariate. The estimation procedure is developed in a parametric framework when there are not only complete data but also incomplete one. The Expectation-Maximization (EM) algorithm is employed to handle the incomplete data problem. Simulation results are presented to illustrate the accuracy and some properties of the estimation results.

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A study on the factors affecting shelf-life for 60, 81mm mortar ammunition (60, 81mm 박격포탄의 저장수명 요인 연구)

  • Jang, SooHee;Chun, Heuiju;Cho, Inho;Yoon, KeunSig;Kang, MinJung;Park, DongSoo
    • The Korean Journal of Applied Statistics
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    • v.31 no.5
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    • pp.611-620
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    • 2018
  • Limitations on human and material resources make it is difficult to conduct Ammunition Stockpile Reliability Program (ASRP) tasks for the entire ammunition. Stockpile ammunition life prediction studies can contribute to efficient ASRP tasks. This study assess the shelf-life of ammunition, using survival analysis based on ASRP results for 60mm and 81mm mortar ammunition from 2003 to 2016. Traditional assessments often use solely storage duration as the only main independent variable; however, this assessment used other factors such as ammunition magazine shape and weather factors with the stockpile shelf-life as independent variables to conduct a Cox's proportional hazard model analysis. This was then followed by an assessment of ammunition magazine type, maximum temperature and rainfall factors influence on the shelf-life of 60mm and 81mm mortar ammunition. As a result, the type of ammunition magazine, maximum temperature and the rainfall influence the shelf-life of 60mm and 81mm mortar ammunition.

Black Hispanic and Black Non-Hispanic Breast Cancer Survival Data Analysis with Half-normal Model Application

  • Khan, Hafiz Mohammad Rafiqullah;Saxena, Anshul;Vera, Veronica;Abdool-Ghany, Faheema;Gabbidon, Kemesha;Perea, Nancy;Stewart, Tiffanie Shauna-Jeanne;Ramamoorthy, Venkataraghavan
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.21
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    • pp.9453-9458
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    • 2014
  • Background: Breast cancer is the second leading cause of cancer death for women in the United States. Differences in survival of breast cancer have been noted among racial and ethnic groups, but the reasons for these disparities remain unclear. This study presents the characteristics and the survival curve of two racial and ethnic groups and evaluates the effects of race on survival times by measuring the lifetime data-based half-normal model. Materials and Methods: The distributions among racial and ethnic groups are compared using female breast cancer patients from nine states in the country all taken from the National Cancer Institute's Surveillance, Epidemiology, and End Results cancer registry. The main end points observed are: age at diagnosis, survival time in months, and marital status. The right skewed half-normal statistical probability model is used to show the differences in the survival times between black Hispanic (BH) and black non-Hispanic (BNH) female breast cancer patients. The Kaplan-Meier and Cox proportional hazard ratio are used to estimate and compare the relative risk of death in two minority groups, BH and BNH. Results: A probability random sample method was used to select representative samples from BNH and BH female breast cancer patients, who were diagnosed during the years of 1973-2009 in the United States. The sample contained 1,000 BNH and 298 BH female breast cancer patients. The median age at diagnosis was 57.75 years among BNH and 54.11 years among BH. The results of the half-normal model showed that the survival times formed positive skewed models with higher variability in BNH compared with BH. The Kaplan-Meir estimate was used to plot the survival curves for cancer patients; this test was positively skewed. The Kaplan-Meier and Cox proportional hazard ratio for survival analysis showed that BNH had a significantly longer survival time as compared to BH which is consistent with the results of the half-normal model. Conclusions: The findings with the proposed model strategy will assist in the healthcare field to measure future outcomes for BH and BNH, given their past history and conditions. These findings may provide an enhanced and improved outlook for the diagnosis and treatment of breast cancer patients in the United States.

Study on the determinants of employment duration in the youth-intern project (중소기업 청년인턴 취업자의 재직기간 분석)

  • Park, Sungik;Ryu, Jangsoo;Kim, Jonghan;Cho, Jangsik
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.2
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    • pp.285-294
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    • 2016
  • In general, employment duration is influenced by the individual characteristics (level-1) as well as type of the occupational characteristics (level-2). That is, the data has hierarchical structure in the sense that individual employment duration is influenced by the individual-level variables (level-1) and the job-level (level-2) variables. In this paper, we study the determinants of the employment duration of youth-intern in the SMEs (small and medium enterprises) using Cox's mixed effect model. Major results at level-1 variables are as followings. First, the hazard rate of treatment group is lower than that of control group. Second, the hazard rate of woman is lower than that of man. Also, the hazard rate is lower, for the older and the workers working in the bigger company. Investigation of level-2 variables has shown that random effect for job-level is statistically significant.

Kernel Estimation of Hazard Ratio Based on Censored Data

  • Choi, Myong-Hui;Lee, In-Suk;Song, Jae-Kee
    • Journal of the Korean Data and Information Science Society
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    • v.12 no.2
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    • pp.125-143
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    • 2001
  • We, in this paper, propose a kernel estimator of hazard ratio with censored survival data. The uniform consistency and asymptotic normality of the proposed estimator are proved by using counting process approach. In order to assess the performance of the proposed estimator, we compare the kernel estimator with Cox estimator and the generalized rank estimators of hazard ratio in terms of MSE by Monte Carlo simulation. Two examples are illustrated for our results.

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