• Title/Summary/Keyword: Censored Data

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Bayesian multiple comparisons in Freund's bivariate exponential populations with type I censored data

  • Cho, Jang-Sik
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.3
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    • pp.569-574
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    • 2010
  • We consider two components system which have Freund's bivariate exponential model. In this case, Bayesian multiple comparisons procedure for failure rates is sug-gested in K Freund's bivariate exponential populations. Here we assume that the com-ponents enter the study at random over time and the analysis is carried out at some prespeci ed time. We derive fractional Bayes factor for all comparisons under non- informative priors for the parameters and calculate the posterior probabilities for all hypotheses. And we select a hypotheses which has the highest posterior probability as best model. Finally, we give a numerical examples to illustrate our procedure.

Estimation of a Product Replacement Ratio During the Warranty Period for a Warranty Analysis (보증분석을 위한 품질보증 기간 중 제품 교체율 추정 사례 연구)

  • Ahn, Hae-Il
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.35 no.2
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    • pp.71-79
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    • 2012
  • In this paper, an evaluation of a product replacement ratio of irreparable items to the normally working ones is performed with a view to a warranty analysis. It is demonstrated that the replacement ratio during the warranty period can be estimated from the field data collected during the period of operation, and one can provide the management with a useful information regarding the appropriateness for the warranty period, which is vital to the product marketing strategy. Although warranty data usually take the form of multiply right censored interval data, the conventional reliability analysis method seems to be good enough as in this case. More sophisticated method such as warranty cost analysis and 2-dimensional warranty analysis is yet desired.

An Exploratory Study on the New Product Demand Curve Estimation Using Online Auction Data

  • Shim Seon-Young;Lee Byung-Tae
    • Management Science and Financial Engineering
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    • v.11 no.3
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    • pp.125-136
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    • 2005
  • As the importance of time-based competition is increasing, information systems for supporting the immediate decision making is strongly required. Especially high -tech product firms are under extreme pressure of rapid response to the demand side due to relatively short life cycle of the product. Therefore, the objective of our research is proposing a framework of estimating demand curve based on e-auction data, which is extremely easy to access and well reflect the limited demand curve in that channel. Firstly, we identify the advantages of using e-auction data for full demand curve estimation and then verify it using Agent-Eased-Modeling and Tobin's censored regression model.

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.

Regression discontinuity for survival data

  • Youngjoo Cho
    • Communications for Statistical Applications and Methods
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    • v.31 no.1
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    • pp.155-178
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    • 2024
  • Regression discontinuity (RD) design is one of the most widely used methods in causal inference for estimation of treatment effect when the treatment is created by a cutpoint from the covariate of interest. There has been little attention to RD design, although it provides a very useful tool for analysis of treatment effect for censored data. In this paper, we define the causal effect for survival function in RD design when the treatment is assigned deterministically by the covariate of interest. We propose estimators of this causal effect for survival data by using transformation, which leads unbiased estimator of the survival function with local linear regression. Simulation studies show the validity of our approach. We also illustrate our proposed method using the prostate, lung, colorectal and ovarian (PLCO) dataset.

Comparison of missing data methods in clustered survival data using Bayesian adaptive B-Spline estimation

  • Yoo, Hanna;Lee, Jae Won
    • Communications for Statistical Applications and Methods
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    • v.25 no.2
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    • pp.159-172
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    • 2018
  • In many epidemiological studies, missing values in the outcome arise due to censoring. Such censoring is what makes survival analysis special and differentiated from other analytical methods. There are many methods that deal with censored data in survival analysis. However, few studies have dealt with missing covariates in survival data. Furthermore, studies dealing with missing covariates are rare when data are clustered. In this paper, we conducted a simulation study to compare results of several missing data methods when data had clustered multi-structured type with missing covariates. In this study, we modeled unknown baseline hazard and frailty with Bayesian B-Spline to obtain more smooth and accurate estimates. We also used prior information to achieve more accurate results. We assumed the missing mechanism as MAR. We compared the performance of five different missing data techniques and compared these results through simulation studies. We also presented results from a Multi-Center study of Korean IBD patients with Crohn's disease(Lee et al., Journal of the Korean Society of Coloproctology, 28, 188-194, 2012).

Predicting the future number of failures based on the field failure summary data (필드 고장 요약 데이터를 활용한 미래 고장수의 예측)

  • Baik, Jai-Wook;Jo, Jin-Nam
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.4
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    • pp.755-764
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    • 2011
  • In many companies field failure data is used to predict the future number of failures, especially when an unexpected failure mode happens to be a problem. It is because they want to predict the number of spare parts needed and the future quality warranty cost associated with the part based on the predictions of the future number of failures. In this paper field summary data is used to predict the future number of failures based on an appropriate distribution. Other types of data are also investigated to identify the appropriate distribution.

Approximate MLE for the Scale Parameter of the Weibull Distribution with Type-II Censoring

  • Kang, Suk-Bok;Kim, Mi-Hwa
    • Journal of the Korean Data and Information Science Society
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    • v.5 no.2
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    • pp.19-27
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    • 1994
  • It is known that the maximum likelihood method does not provide explicit estimator for the scale parameter of the Weibull distribution based on Type-II censored samples. In this paper we provide an approximate maximum likelihood estimator (AMLE) of the scale parameter of the Weibull distribution with Type-II censoring. We obtain the asymptotic variance and simulate the values of the bias and the variance of this estimator based on 3000 Monte Carlo runs for n = 10(10)30 and r,s = 0(1)4. We also simulate the absolute biases of the MLE and the proposed AMLE for complete samples. It is found that the absolute bias of the AMLE is smaller than the absolute bias of the MLE.

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Bayesian Survival Estimation of Pareto Distribution of the Second Kind Based on Type II Censored Data

  • Kim, Dal-Ho;Lee, Woo-Dong;Kang, Sang-Gil
    • Communications for Statistical Applications and Methods
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    • v.12 no.3
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    • pp.729-742
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    • 2005
  • In this paper, we discuss the propriety of the various noninformative priors for the Pareto distribution. The reference prior, Jeffreys prior and ad hoc noninformative prior which is used in several literatures will be introduced and showed that which prior gives the proper posterior distribution. The reference prior and Jeffreys prior give a proper posterior distribution, but ad hoc noninformative prior which is proportional to reciprocal of the parameters does not give a proper posterior. To compute survival function, we use the well-known approximation method proposed by Lindley (1980) and Tireney and Kadane (1986). And two methods are compared by simulation. A real data example is given to illustrate our methodology.

Nonparametric Tests for Monotonicity Properties of Mean Residual Life Function

  • Jeon, Jong-Woo;Park, Dong-Ho
    • Journal of the Korean Statistical Society
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    • v.26 no.1
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    • pp.101-116
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    • 1997
  • This is primarily an expository paper that presents several nonparametric procedures for testing exponentiality against certain monotonicity properties of the mean residual life function, tests against the trend change in such function attract a great deal of attention of late in reliability analysis. In this note, we present some of the known testing procedures regarding the behavior of mean residual life function. These tests are also compared in terms of asymptotic relative efficiency and empirical power against a few alternatives. The tests based on incomplete data are also briefly discussed.

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