• 제목/요약/키워드: Cox proportional hazards model

검색결과 164건 처리시간 0.026초

비례위험모형의 적합도 검정법에 관한 연구 (A study on the goodness-of-fit tests for proportional hazards model)

  • 장애방;이재원
    • 응용통계연구
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    • 제10권1호
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    • pp.85-104
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    • 1997
  • Cox(1972)가 제안한 비례위험모형은 두 표본의 처리를 비교하거나 공변량의 효과와 생존시간의 관계를 회귀적으로 해석하는 등 다양한 상황에 쓰일 수 있어 널리 이용되고 있다. 따라서 비례위험모형에 대하여 많은 통계 학자들이 연구를 하였는데, 그중에서도 적합도 검정법에 대하여 여러 편의 논문이 발표되었다. 본 논문에서는 지금까지 제안된 비례위험모형에 대한 적합도 검정법에 관하여 설명하고, 다양한 형태의 자료에 대한 모의실험을 통하여 비례위험모형을 이용하여 생존분석을 실시하려는 통계분석가들에게 도움이 되도록 각각의 특성에 관하여 논의하였다.

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Prognostic Factors for Survival in Patients with Breast Cancer Referred to Omitted Cancer Research Center in Iran

  • Baghestani, Ahmad Reza;Shahmirzalou, Parviz;Zayeri, Farid;Akbari, Mohammad Esmaeil;Hadizadeh, Mohammad
    • Asian Pacific Journal of Cancer Prevention
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    • 제16권12호
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    • pp.5081-5084
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    • 2015
  • Background: Breast cancer is a malignant tumor that starts from cells of the breast and is seen mainly in women. It's the most common cancer in women worldwide and is a major threat to health. The purpose of this study was to fit a Cox proportional hazards model for prediction and determination of years of survival in Iranian patients. Materials and Methods: A total of 366 patients with breast cancer in the Cancer Research Center were included in the study. A Cox proportional hazard model was used with variables such as tumor grade, number of removed positive lymph nodes, human epidermal growth factor receptor 2 (HER2) expression and several other variables. Kaplan-Meier curves were plotted and multi-years of survival were evaluated. Results: The mean age of patients was 48.1 years. Consumption of fatty foods (p=0.033), recurrence (p<0.001), tumor grade (p=0.046) and age (p=0.017) were significant variables. The overall 1- year, 3-year and 5-year survival rates were found to be 93%, 75% and 52%. Conclusions: Use of covariates and the Cox proportional hazard model are effective in predicting the survival of individuals and this model distinguished 4 effective factors in the survival of patients.

한국 성인의 근감소증 위험도 평가점수 모형 개발 (Developing the Sarcopenia Risk Assessment Model in Korean Adults)

  • 배은정;박일수
    • 한국학교ㆍ지역보건교육학회지
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    • 제23권4호
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    • pp.81-93
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    • 2022
  • Objectives: The purpose of this study was to develop a model for comprehensively evaluating the risk of sarcopenia in Korean adults and to generate the sarcopenia risk scorecard model based on the results. Methods: The participants of the study were 7,118 adults without sarcopenia in the first basic survey, and a longitudinal analysis was conducted using data from the 1st to 8th survey (2006-2020) of the Korean Longitudinal Study of Aging (KLoSA). The data were analyzed using Rao-Scott chi-square test and weighted Cox proportional hazards regression of complex sampling design. The sarcopenia risk scorecard model was developed by Cox proportional hazards regression using points to double the odds (PDO) method. Results: The findings show that the risk factors for sarcopenia in Korean adults were gender, age, marital status, socioeconomic status, body mass index (BMI), regular exercise, diabetes and arthritis diagnosis. In the scorecard results, the case of exposure to the highest risk level was 100 points. The highest score range were given in the order of age over 65, low BMI, and low socioeconomic status. Conclusions: The significance of this study is that the causal relationship between various factors and the occurrence of sarcopenia in Korean adults was identified. Also, the model developed in this study is expected to be useful in detecting participants with risk of sarcopenia in the community early and preventing and managing sarcopenia through appropriate health education.

Bayesian Variable Selection in the Proportional Hazard Model

  • Lee, Kyeong-Eun
    • Journal of the Korean Data and Information Science Society
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    • 제15권3호
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    • pp.605-616
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    • 2004
  • In this paper we consider the proportional hazard models for survival analysis in the microarray data. For a given vector of response values and gene expressions (covariates), we address the issue of how to reduce the dimension by selecting the significant genes. In our approach, rather than fixing the number of selected genes, we will assign a prior distribution to this number. To implement our methodology, we use a Markov Chain Monte Carlo (MCMC) method.

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Cox 비례위험모형을 따르는 중도절단자료 생성 (Generating censored data from Cox proportional hazards models)

  • 김지현;김봉성
    • 응용통계연구
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    • 제31권6호
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    • pp.761-769
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    • 2018
  • 통계학 연구에 모의실험이 중요하게 쓰이며 중도절단자료를 다루는 생존분석에서도 마찬가지다. 생존분석에서 Cox 모형이 널리 쓰이는데, Cox 모형을 따르는 중도절단자료를 생성하는 방법에 대해 살펴보았다. Bender 등 (Statistics in Medicine, 24, 1713-1723, 2005)은 생존시간을 생성하는 모수적 방법을 제시하였으나 생존시간뿐만 아니라 중도절단시간도 생성해야 중도절단자료를 얻게 된다. 중도절단자료를 생성하기 위한 모수적 방법과 함께 비모수적 방법도 제시하였으며 실제 자료에도 적용해 보았다.

Cox Model 을 이용한 공기압 실린더의 수명예측에 관한 연구 (A Study on Life Prediction of Pneumatic Cylinder using Cox Model)

  • 강보식;김형의;장무성
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2008년도 추계학술대회A
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    • pp.1387-1390
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    • 2008
  • Pneumatic cylinder is widely used in the various industrial fields. Reliability Study of this field is very important part to the related companies. In this study, we want to predict the life of pneumatic cylinder using Cox (or proportional hazards) model. Used in biomedical applications, the Cox model can be used as an accelerated life testing model. We considered working pressure and temperature as stress factors. The statistical software is used to analyze and forecast the life data.

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Comparison between Parametric and Semi-parametric Cox Models in Modeling Transition Rates of a Multi-state Model: Application in Patients with Gastric Cancer Undergoing Surgery at the Iran Cancer Institute

  • Zare, Ali;Mahmoodi, Mahmood;Mohammad, Kazem;Zeraati, Hojjat;Hosseini, Mostafa;Naieni, Kourosh Holakouie
    • Asian Pacific Journal of Cancer Prevention
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    • 제14권11호
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    • pp.6751-6755
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    • 2013
  • Background: Research on cancers with a high rate of mortality such as those occurring in the stomach requires using models which can provide a closer examination of disease processes and provide researchers with more accurate data. Various models have been designed based on this issue and the present study aimed at evaluating such models. Materials and Methods: Data from 330 patients with gastric cancer undergoing surgery at Iran Cancer Institute from 1995 to 1999 were analyzed. Cox-Snell Residuals and Akaike Information Criterion were used to compare parametric and semi-parametric Cox models in modeling transition rates among different states of a multi-state model. R 2.15.1 software was used for all data analyses. Results: Analysis of Cox-Snell Residuals and Akaike Information Criterion for all probable transitions among different states revealed that parametric models represented a better fitness. Log-logistic, Gompertz and Log-normal models were good choices for modeling transition rate for relapse hazard (state $1{\rightarrow}state$ 2), death hazard without a relapse (state $1{\rightarrow}state$ 3) and death hazard with a relapse (state $2{\rightarrow}state$ 3), respectively. Conclusions: Although the semi-parametric Cox model is often used by most cancer researchers in modeling transition rates of multistate models, parametric models in similar situations- as they do not need proportional hazards assumption and consider a specific statistical distribution for time to occurrence of next state in case this assumption is not made - are more credible alternatives.

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

  • Kim Jong-woon;Eo Seong-phil
    • 한국신뢰성학회:학술대회논문집
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    • 한국신뢰성학회 2005년도 학술발표대회 논문집
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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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Bootstrap Confidence Intervals for an Adjusted Survivor Function under the Dependent Censoring Model

  • Lee, Seung-Yeoun;Sok, Yong-U
    • Communications for Statistical Applications and Methods
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    • 제8권1호
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    • pp.127-135
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    • 2001
  • In this paper, we consider a simple method for testing the assumption of independent censoring on the basis of a Cox proportional hazards regression model with a time-dependent covariate. This method involves a two-stage sampling in which a random subset of censored observations is selected and followed-up until their true survival times are observed. Lee and Wolfe(1998) proposed an adjusted estimate of the survivor function for the dependent censoring under a proportional hazards alternative. This paper extends their result to obtain a bootstrap confidence interval for the adjusted survivor function under the dependent censoring. The proposed procedure is illustrated with an example of a clinical trial for lung cancer analysed in Lee and Wolfe(1998).

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