• Title/Summary/Keyword: Right Censored Data

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A two-sample test with interval censored competing risk data using multiple imputation (다중대체방법을 이용한 구간 중도 경쟁 위험 모형에서의 이표본 검정)

  • Kim, Yuwon;Kim, Yang-Jin
    • The Korean Journal of Applied Statistics
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    • v.30 no.2
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    • pp.233-241
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    • 2017
  • Interval censored data frequently occur in observation studies where the subject is followed periodically. In this paper, our interest is to suggest a test statistic to compare the CIF of two groups with interval censored failure time data in the presence of competing risks. Gray (1988) suggested a test statistic for right censored data that motivated a well-known Fine and Gray's subdistribution hazard model. A multiple imputation technique is adopted to adopt Gray's test statistic to interval censored data. The powers and sizes of the suggested method are investigated through diverse simulation schemes. The main merit of the suggested method is its simplicity to implement with existing software for right censored data. The method is illustrated by analyzing Bangkok's HIV cohort dataset.

Semiparametric accelerated failure time model for the analysis of right censored data

  • Jin, Zhezhen
    • Communications for Statistical Applications and Methods
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    • v.23 no.6
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    • pp.467-478
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    • 2016
  • The accelerated failure time model or accelerated life model relates the logarithm of the failure time linearly to the covariates. The parameters in the model provides a direct interpretation. In this paper, we review some newly developed practically useful estimation and inference methods for the model in the analysis of right censored data.

Nonparametric Regression with Left-Truncated and Right-Censored Data

  • Park, Jinho
    • Communications for Statistical Applications and Methods
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    • v.6 no.3
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    • pp.791-800
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    • 1999
  • Gross and Lai(1996) proposed a new approach for ordinary regression with left-truncated and right-censored (I.t.r.c) data. This paper shows how to apply nonparametric algorithms such as multivariate adaptive regression splines to 1.t.r.c data.

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Two-step LS-SVR for censored regression

  • Bae, Jong-Sig;Hwang, Chang-Ha;Shim, Joo-Yong
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.2
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    • pp.393-401
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    • 2012
  • This paper deals with the estimations of the least squares support vector regression when the responses are subject to randomly right censoring. The estimation is performed via two steps - the ordinary least squares support vector regression and the least squares support vector regression with censored data. We use the empirical fact that the estimated regression functions subject to randomly right censoring are close to the true regression functions than the observed failure times subject to randomly right censoring. The hyper-parameters of model which affect the performance of the proposed procedure are selected by a generalized cross validation function. Experimental results are then presented which indicate the performance of the proposed procedure.

Failure Data Error according to Characteristics of One-Shot Weapon System and its Solution (일회성 무기체계 특성에 따른 고장 데이터의 오차 및 극복방안)

  • Choi, Yunsuk;Ma, Jungmok
    • Journal of the Korea Institute of Military Science and Technology
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    • v.21 no.5
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    • pp.599-606
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    • 2018
  • Failure data of systems in many field can be erroneous, which influences the reliability analysis of the systems. The general form of failure data is right censored data with accurate time information. But due to its nature of data collection in the military field, failure time of one-shot weapon systems can have errors which are related to the maintenance period. So this paper suggests a model that can reduce the error by utilizing interval censored data as an alternative to right censored data in weibull distribution.

Additive Regression Models for Censored Data (중도절단된 자료에 대한 가법회귀모형)

  • Kim, Chul-Ki
    • Journal of Korean Society for Quality Management
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    • v.24 no.1
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    • pp.32-43
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    • 1996
  • In this paper we develop nonparametric methods for regression analysis when the response variable is subject to censoring that arises naturally in quality engineering. This development is based on a general missing information principle that enables us to apply, via an iterative scheme, nonparametric regression techniques for complete data to iteratively reconstructed data from a given sample with censored observations. In particular, additive regression models are extended to right-censored data. This nonparametric regression method is applied to a simulated data set and the estimated smooth functions provide insights into the relationship between failure time and explanatory variables in the data.

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Robust Regression and Stratified Residuals for Left-Truncated and Right-Censored Data

  • Kim, Chul-Ki
    • Journal of the Korean Statistical Society
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    • v.26 no.3
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    • pp.333-354
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    • 1997
  • Computational algorithms to calculate M-estimators and rank estimators of regression parameters from left-truncated and right-censored data are developed herein. In the case of M-estimators, new statistical methods are also introduced to incorporate leverage assements and concomitant scale estimation in the presence of left truncation and right censoring on the observed response. Furthermore, graphical methods to examine the residuals from these data are presented. Two real data sets are used for illustration.

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A Case Study of Reliability Assessment of CMC in Hydraulic Clutch System with Field Warranty Data (보증수리자료를 활용한 유압클러치시스템의 클러치마스터실린더 신뢰성 분석 사례연구)

  • Lee, Sang Cheon;Park, Jong Hun
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.36 no.3
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    • pp.1-7
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    • 2013
  • This paper is a case study of reliability assessment with field warranty data of Clutch Master Cylinder (CMC) in hydraulic clutch system. We estimate lifetime distribution using field warranty data which contain much useful information for understanding reliability of the system in the real-world environments. However, the estimated parameters are far from existing reference values, which seems to be caused right censored field warranty data. To modify the parameters, we use the information of the durability test which is performed to verify that the lifetime of the item meets the required level. After that, we can observe that the modified parameters are closer to the existing reference values. This case study shows a possible idea to supplement lack of right censored field warranty data and its applicability.

Efficient Score Estimation and Adaptive Rank and M-estimators from Left-Truncated and Right-Censored Data

  • Chul-Ki Kim
    • Communications for Statistical Applications and Methods
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    • v.3 no.3
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    • pp.113-123
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    • 1996
  • Data-dependent (adaptive) choice of asymptotically efficient score functions for rank estimators and M-estimators of regression parameters in a linear regression model with left-truncated and right-censored data are developed herein. The locally adaptive smoothing techniques of Muller and Wang (1990) and Uzunogullari and Wang (1992) provide good estimates of the hazard function h and its derivative h' from left-truncated and right-censored data. However, since we need to estimate h'/h for the asymptotically optimal choice of score functions, the naive estimator, which is just a ratio of estimated h' and h, turns out to have a few drawbacks. An altermative method to overcome these shortcomings and also to speed up the algorithms is developed. In particular, we use a subroutine of the PPR (Projection Pursuit Regression) method coded by Friedman and Stuetzle (1981) to find the nonparametric derivative of log(h) for the problem of estimating h'/h.

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Multivariate Nonparametric Tests for Grouped and Right Censored Data

  • Park Hyo-Il;Na Jong-Hwa;Hong Seungman
    • International Journal of Reliability and Applications
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    • v.6 no.1
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    • pp.53-64
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    • 2005
  • In this paper, we propose a nonparametric test procedure for the multivariate, grouped and right censored data for two sample problem. For the construction of the test statistic, we use the linear rank statistics for each component and apply the permutation principle for obtaining the null distribution. For the large sample case, the asymptotic distribution is derived under the null hypothesis with the additional assumption that two censoring distributions are also equal. Finally, we illustrate our procedure with an example and discuss some concluding remarks. In appendices, we derive the expression of the covariance matrix and prove the asymptotic distribution.

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