• 제목/요약/키워드: likelihood interval

검색결과 194건 처리시간 0.024초

Meta-analysis of Associations of the Ezrin Gene with Human Osteosarcoma Response to Chemotherapy and Prognosis

  • Wang, Zhe;He, Mao-Lin;Zhao, Jin-Min;Qing, Hai-Hui;Wu, Yang
    • Asian Pacific Journal of Cancer Prevention
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    • 제14권5호
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    • pp.2753-2758
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    • 2013
  • Various studies examining the relationship between Ezrin overexpression and response to chemotherapy and clinical outcome in patients with osteosarcoma have yielded inconclusive results. We accordingly conducted a meta-analysis of 7 studies (n = 318 patients) that evaluated the correlation between Ezrin and histologic response to chemotherapy and clinical prognosis (death). Data were synthesized in receiver operating characteristic curves and with fixed-effects and random-effects likelihood ratios and risk ratios. Quantitative synthesis showed that Ezrin is not a prognostic factor for the response to chemotherapy. The positive likelihood ratio was 0.538 (95% confidence interval [95% CI], 0.296- 0.979; random-effects calculation), and the negative likelihood ratio was 2.151 (95% CI, 0.905- 5.114; random-effects calculations). There was some between-study heterogeneity, but no study showed strong discriminating ability. Conversely, Ezrin positive status tended to be associated with a lower 2-year survival (risk ratio, 2.45; 95% CI, 1.26-4.76; random-effects calculation) with some between-study heterogeneity that disappeared when only studies that employed immunohistochemistry were considered (risk ratio, 2.97; 95% CI, 2.01- 4.40; fixed-effects calculation). To conclude, Ezrin is not associated with the histologic response to chemotherapy in patients with osteosarcoma, whereas Ezrin positivity was associated with a lower 2-year survival rate regarding risk of death at 2 years. Expression change of Ezrin is an independent prognostic factor in patients with osteosarcoma.

결측되었거나 구간중도절단된 중간사건을 가진 준경쟁적위험 자료에 대한 가산위험모형 (Additive hazards models for interval-censored semi-competing risks data with missing intermediate events)

  • 김자연;김진흠
    • 응용통계연구
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    • 제30권4호
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    • pp.539-553
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    • 2017
  • 본 논문에서는 사망과 같은 종말사건의 발생 유무는 알고 있지만 치매 발병과 같은 중간사건이 구간중도절단 되었거나 연구 기간 도중에 추적이 끊겨 결측된 준경쟁적위험 자료에 대해 다중상태모형을 적용하여 모수를 추정하는 방법을 제안하였다. 이를 위해 본 논문에서는 상태 간의 전이강도는 로그정규 프레일티를 랜덤효과로 가진 Lin과 Ying(1994)의 가산위험모형을 따른다고 가정하였다. 다섯 가지 상태를 가진 다중상태모형에서 가능한 여섯 가지 경로별로 조건부우도를 정의하였고, 주변우도를 구하기 위해 조정중요표본추출법을 적용하였으며 반복유사뉴튼 방법으로 최적해를 구하였다. 소표본 모의실험을 통해 모수의 95% 신뢰구간 포함률이 명목값에 얼마나 가까운지 살펴보았으며, 제안한 모형을 Persones $Ag{\acute{e}}es$ Quid (PAQUID) 자료 (Helmer 등, 2001)에 적용하고 그 결과를 해석하였다.

붓스트랩 방법을 이용한 일반화 자기회귀 조건부 이분산모형에서의 조건부 분산 예측 (Prediction of Conditional Variance under GARCH Model Based on Bootstrap Methods)

  • 김희영;박만식
    • Communications for Statistical Applications and Methods
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    • 제16권2호
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    • pp.287-297
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    • 2009
  • 일반적으로 일반화 자기회귀 조건부 이분산(GARCH)모형 하에서, 우도함수에 기반한 자료의 예측구간의 추정은 오차항의 분포에 민감하게 반응하고 더욱이 조건부분산의 경우 구간추정이 현실적으로 쉽게 풀리지 않는 문제이다. 이를 해결하기 위해 붓스트랩방법(bootstrap method)이 적용될 수 있음을 최근 연구들을 통해 밝혀졌다. 본 논문에서는 GARCH모형 하에서 자료와 변동성(조건부 분산)의 예측구간 추정을 위해 최근 소개된 Pascual 등 (2006)의 논문을 토대로 붓스트랩 방법를 정리하였다 실제 사례분석을 위해 국내 주가수익률자료를 이용하였다.

레일리 페이딩 채널에서의 이중직교 신호에 대한 다중심볼 검파 (Multi-symbol detection for biorthogonal signals over rayleigh fading channels)

  • 엄의식;윤순영;이황수
    • 한국통신학회논문지
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    • 제22권1호
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    • pp.30-39
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    • 1997
  • 본 논문은 CDMA 셀룰라 역방향 접속 시스템의 성능개선을 위하여 이중직교 신호에 대한 다중심볼 검파방식을 제안하고, 이에 대한 성능해석과 컴퓨터 모의실험을 수행한다. 이 방식은 기존의 심볼단위 비동기 검파대신 복잡도를 줄인 근사 MLSE에 의해 다중심볼로 구성된 복조 데이터와 채널을 동시에 예측한다. 이 방식은 또한 주어진 심볼의 워드수 M에 대해 관측하는 다중심볼 길이 N을 적절히 선택할 때 채널의 예측이 없이도 이상적인 동기검파 방식에 근접한 오류성능을 얻게 해준다. 특히 매우 의미 있는 사항은 이 방식을 CDMA 역방향 접속 시스템에 적용할 때 요구되는 평균 비트당 신호대 잡은 전력비 ${\gamma}_{b}$를 약 1.4dB정도 줄일 수 있어 38% 정도의 용량이 증가된다.

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RELIABILITY ANALYSIS FOR THE TWO-PARAMETER PARETO DISTRIBUTION UNDER RECORD VALUES

  • Wang, Liang;Shi, Yimin;Chang, Ping
    • Journal of applied mathematics & informatics
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    • 제29권5_6호
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    • pp.1435-1451
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    • 2011
  • In this paper the estimation of the parameters as well as survival and hazard functions are presented for the two-parameter Pareto distribution by using Bayesian and non-Bayesian approaches under upper record values. Maximum likelihood estimation (MLE) and interval estimation are derived for the parameters. Bayes estimators of reliability performances are obtained under symmetric (Squared error) and asymmetric (Linex and general entropy (GE)) losses, when two parameters have discrete and continuous priors, respectively. Finally, two numerical examples with real data set and simulated data, are presented to illustrate the proposed method. An algorithm is introduced to generate records data, then a simulation study is performed and different estimates results are compared.

New Family of the Exponential Distributions for Modeling Skewed Semicircular Data

  • Kim, Hyoung-Moon
    • 응용통계연구
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    • 제22권1호
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    • pp.205-220
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    • 2009
  • For modeling skewed semicircular data, we derive new family of the exponential distributions. We extend it to the l-axial exponential distribution by a transformation for modeling any arc of arbitrary length. It is straightforward to generate samples from the f-axial exponential distribution. Asymptotic result reveals two things. The first is that linear exponential distribution can be used to approximate the l-axial exponential distribution. The second is that the l-axial exponential distribution has the asymptotic memoryless property though it doesn't have strict memoryless property. Some trigonometric moments are also derived in closed forms. Maximum likelihood estimation is adopted to estimate model parameters. Some hypotheses tests and confidence intervals are also developed. The Kolmogorov-Smirnov test is adopted for goodness of fit test of the l-axial exponential distribution. We finally obtain a bivariate version of two kinds of the l-axial exponential distributions.

CONFIDENCE INTERVALS ON THE AMONG GROUP VARIANCE COMPONENT IN A REGRESSION MODEL WITH AN UNBALANCED ONE-FOLD NESTED ERROR STRUCTURE

  • 박동준
    • 한국통계학회:학술대회논문집
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    • 한국통계학회 2002년도 추계 학술발표회 논문집
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    • pp.141-146
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    • 2002
  • In this article we consider the problem of constructing confidence intervals for a linear regression model with nested error structure. A popular approach is the likelihood-based method employed by PROC MIXED of SAS. In this paper, we examine the ability of MIXED to produce confidence intervals that maintain the stated confidence coefficient. Our results suggest the intervals for the regression coefficients work well, but the intervals for the variance component associated with the primary level cannot be recommended. Accordingly, we propose alternative methods for constructing confidence intervals on the primary level variance component. Computer simulation is used to compare the proposed methods. A numerical example and SAS code are provided to demonstrate the methods.

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Parametric inference on step-stress accelerated life testing for the extension of exponential distribution under progressive type-II censoring

  • El-Dina, M.M. Mohie;Abu-Youssef, S.E.;Ali, Nahed S.A.;Abd El-Raheem, A.M.
    • Communications for Statistical Applications and Methods
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    • 제23권4호
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    • pp.269-285
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    • 2016
  • In this paper, a simple step-stress accelerated life test (ALT) under progressive type-II censoring is considered. Progressive type-II censoring and accelerated life testing are provided to decrease the lifetime of testing and lower test expenses. The cumulative exposure model is assumed when the lifetime of test units follows an extension of the exponential distribution. Maximum likelihood estimates (MLEs) and Bayes estimates (BEs) of the model parameters are also obtained. In addition, a real dataset is analyzed to illustrate the proposed procedures. Approximate, bootstrap and credible confidence intervals (CIs) of the estimators are then derived. Finally, the accuracy of the MLEs and BEs for the model parameters is investigated through simulation studies.

On prediction of random effects in log-normal frailty models

  • Ha, Il-Do;Cho, Geon-Ho
    • Journal of the Korean Data and Information Science Society
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    • 제20권1호
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    • pp.203-209
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    • 2009
  • Frailty models are useful for the analysis of correlated and/or heterogeneous survival data. However, the inferences of fixed parameters, rather than random effects, have been mainly studied. The prediction (or estimation) of random effects is also practically useful to investigate the heterogeneity of the hospital or patient effects. In this paper we propose how to extend the prediction method for random effects in HGLMs (hierarchical generalized linear models) to log-normal semiparametric frailty models with nonparametric baseline hazard. The proposed method is demonstrated by a simulation study.

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비례위험모형에서 정보적 중도절단의 효과 (Effects of Informative Censoring in the Proportional Hazards Model)

  • 정대현;홍승만;원동유
    • 한국신뢰성학회지:신뢰성응용연구
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    • 제2권2호
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    • pp.121-133
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    • 2002
  • This paper concerns informative censoring and some of the difficulties it creates in analysis of survival data. For analyzing censored data, misclassification of informative censoring into random censoring is often unavoidable. It is worthwhile to investigate the impact of neglecting informative censoring on the estimation of the parameters of the proportional hazards model. The proposed model includes a primary failure which can be censored informatively or randomly and a followup failure which may be censored randomly. Simulation shows that the loss is about 30% with regard to the confidence interval if we neglect the informative censoring.

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