共查询到20条相似文献,搜索用时 28 毫秒
1.
Olivier Lopez 《统计学通讯:理论与方法》2013,42(15):2639-2660
In a regression model with univariate censored responses, a new estimator of the joint distribution function of the covariates and response is proposed, under the assumption that the response and the censoring variable are independent conditionally to the covariates. This estimator is based on the conditional Kaplan–Meier estimator of Beran (1981), and happens to be an extension of the multivariate empirical distribution function used in the uncensored case. We derive asymptotic i.i.d. representations for the integrals with respect to the measure defined by this estimated distribution function. These representations hold even in the case where the covariates are multidimensional under some additional assumption on the censoring. Applications to censored regression and to density estimation are considered. 相似文献
2.
《统计学通讯:理论与方法》2013,42(10):2043-2052
Abstract Chiu [Chiu, S. N. (1999). An unbiased estimator for the survival function of censored data. Commun. Statist. - Theory Meth. 28(9):2249–2260.] proposed a nonparametric estimator for the survival function which is based on observable censoring times in the general censoring model. His estimator is less efficient than the Product-Limit estimator. Considering an informative censoring model this drawback can partially be overcome. This is shown by a nonparametric, uniformly consistent estimator based on observable censoring times within the simple Koziol–Green model. Some asymptotic properties of the new estimator are investigated and it is compared with the well-known ACL-estimator. 相似文献
3.
Boardman and Kendell (1970) considered the problem of estimation with respect to Type-I censoring when an item is subjected to only one of the two causes of failure assuming exponential model. Patel and Gajjar (1992) considered extension of the Boardman and Kendell's results in case of two-stage progressive censoring. Here we have considered geometric competing risk failure model with two independent causes of failures. Maximum likelihood estimation of the parameters is carried out using Type-I two-stage progressively censored and group censored samples. Asymptotic standard errors of the estimators are obtained for both the cases. Two illustrative examples are cited for ungroup and group competing risk models. 相似文献
4.
Pao-Sheng Shen 《统计学通讯:理论与方法》2013,42(16):4812-4823
ABSTRACTGandy and Jensen (2005) proposed goodness-of-fit tests for Aalen's additive risk model. In this article, we demonstrate that the approach of Gandy and Jensen (2005) can be applied to left-truncated right-censored (LTRC) data and doubly censored data. A simulation study is conducted to investigate the performance of the proposed tests. The proposed tests are illustrated using heart transplant data. 相似文献
5.
Liang Wang 《统计学通讯:理论与方法》2013,42(8):2378-2391
AbstractFor a general censoring scheme called “middle censoring” scheme which was proposed by Jammalamadaka and Mangalam (2003) in nonparametric set up. In this article, point and interval estimation problems are considered for the exponential distribution when the failure data is middle censored with two independent competing failure risks. Different methods are introduced to estimate the unknown model parameters such as maximum likelihood estimation, midpoint approximation, equivalent quantities estimation. The Bayesian estimation is also considered with gamma priors. Two numerical examples are analyzed to show the performance of the proposed methods. 相似文献
6.
ABSTRACTCompeting risks data are common in medical research in which lifetime of individuals can be classified in terms of causes of failure. In survival or reliability studies, it is common that the patients (objects) are subjected to both left censoring and right censoring, which is refereed as double censoring. The analysis of doubly censored competing risks data in presence of covariates is the objective of this study. We propose a proportional hazards model for the analysis of doubly censored competing risks data, using the hazard rate functions of Gray (1988), while focusing upon one major cause of failure. We derive estimators for regression parameter vector and cumulative baseline cause specific hazard rate function. Asymptotic properties of the estimators are discussed. A simulation study is conducted to assess the finite sample behavior of the proposed estimators. We illustrate the method using a real life doubly censored competing risks data. 相似文献
7.
Nezhat Shakeri 《统计学通讯:理论与方法》2013,42(5):777-790
Left censoring concept has been defined in different ways in statistical applications. Turnbull (1974) defines it in a particular way. Whereas in recent literature, especially in epidemiological studies, it has been defined in another way. This difference between the two approaches is the main reason that despite simplicity, Turnbull method cannot be applicable in all cases of doubly censored data. In this article we present a modified Turnbull method for analysis of doubly censored data adequate with recent definition. Comparison has been done with other statistical methods, including imputation estimator, full likelihood-based and conditional likelihood-based approach using Iranian HIV data. 相似文献
8.
The generalized inverse Weibull distribution is a newlife time probability distribution which can be used to model a variety of failure characteristics. It has several desirable properties and nice physical interpretations which enable them to be used frequently. In this article, we present a chi-squared goodness-of-fit test for an accelerated failure time (AFT) model with generalized inverse Weibull distribution (GIW) as the baseline distribution, in both of complete and censored data. This test is based on a modification of the NRR (Nikulin-Rao-Robson) statistic Y2, proposed by Bagdonavicius and Nikulin (2011), for censored data. Two applications of real data are given to illustrate the potentiality of the proposed test. 相似文献
9.
Analysis of discrete lifetime data under middle-censoring and in the presence of covariates 总被引:1,自引:0,他引:1
S. Rao Jammalamadaka 《Journal of applied statistics》2015,42(4):905-913
‘Middle censoring’ is a very general censoring scheme where the actual value of an observation in the data becomes unobservable if it falls inside a random interval (L, R) and includes both left and right censoring. In this paper, we consider discrete lifetime data that follow a geometric distribution that is subject to middle censoring. Two major innovations in this paper, compared to the earlier work of Davarzani and Parsian [3], include (i) an extension and generalization to the case where covariates are present along with the data and (ii) an alternate approach and proofs which exploit the simple relationship between the geometric and the exponential distributions, so that the theory is more in line with the work of Iyer et al. [6]. It is also demonstrated that this kind of discretization of life times gives results that are close to the original data involving exponential life times. Maximum likelihood estimation of the parameters is studied for this middle-censoring scheme with covariates and their large sample distributions discussed. Simulation results indicate how well the proposed estimation methods work and an illustrative example using time-to-pregnancy data from Baird and Wilcox [1] is included. 相似文献
10.
Shu-Fei Wu 《统计学通讯:模拟与计算》2013,42(7):2056-2064
ABSTRACTIn this paper, a modified one-stage multiple comparison procedures with a control for exponential location parameters based on the doubly censored sample under heteroscedasticity is proposed. A simulation study is done and the results show that the proposed procedures have shorter confidence length with coverage probabilities closer to the nominal ones compared with the one proposed in Wu (2017). At last, an example of comparing the duration of remission for four drugs as the treatment of leukemia is given to demonstrate the proposed procedures. 相似文献
11.
12.
Pao-Sheng Shen 《统计学通讯:模拟与计算》2013,42(10):2295-2307
Cai and Zeng (2011) proposed an additive mixed effect model to analyze clustered right-censored data. In this article, we demonstrate that the approach of Cai and Zeng (2011) can be extended to clustered doubly censored data. Furthermore, when both left- and right-censoring variables are always observed, we propose alternative estimators using the approach of Cai and Cheng (2004). A simulation study is conducted to investigate the performance of the proposed estimators. 相似文献
13.
Elham Mirfarah 《统计学通讯:理论与方法》2014,43(10-12):2169-2182
In this article, the Pitman closeness of upper and lower k-records to progressive Type-II censored order statistics for location-scale families is investigated. In each case, the special properties of the probability of Pitman closeness are obtained and the corresponding monotonicity properties are discussed. Moreover, the closest k-record to a specific progressive Type-II censored data is obtained. Finally, for the standard exponential and standard uniform distributions, explicit expressions for the probability of Pitman closeness are derived. For various censoring schemes, the results of the numerical computations are displayed in tables. Most of the results in Ahmadi and Balakrishnan (2013) can be achieved as special cases. 相似文献
14.
Pao-Sheng Shen 《Journal of applied statistics》2011,38(4):675-682
Double censoring arises when T represents an outcome variable that can only be accurately measured within a certain range, [L, U], where L and U are the left- and right-censoring variables, respectively. In this note, using Martingale arguments of Chen et al. [3], we propose an estimator (denoted by ?β) for estimating regression coefficients of transformation model when L is always observed. Under Cox proportional hazards model, the proposed estimator is equivalent to the partial likelihood estimator for left-truncated and right-censored data if the left-censoring variables L were regarded as left-truncated variables. In this case, the estimator ?β can be obtained by the standard software. A simulation study is conducted to investigate the performance of ?β. For the purpose of comparison, the simulation study also includes the estimator proposed by Cai and Cheng [2] for the case when L and U are always observed. 相似文献
15.
Ran Wang 《统计学通讯:理论与方法》2013,42(21):6342-6356
ABSTRACTThis article considers inference for partial linear models with right censored data. We use empirical likelihood based on the Buckley and James (1979) estimating equation to derive the confidence region for the regression parameter. We introduce an adjusted empirical likelihood ratio statistic for the parameter of interest and show that its limiting distribution is standard chi-square. A simulation is carried out to compare our method with the synthetic data approach in Wang and Li (2002). 相似文献
16.
Mixtures of distributions arise frequently in the context of life testing experiments, where one also encounters the problem of censored data. In this article, we derive the locally most powerful (LMP) test for testing the mixing proportion in a general mixture model based on type-I censored data. We also prove the additional properties of unbiasedness and locally maximin using a novel approach. To this end, we prove an extension of a standard lemma in the testing literature (Lehmann, 1986) relating to families with monotone likelihood ratio. 相似文献
17.
Engakkattu Purushothaman Sreedevi Paduthol Godan Sankaran Isha Dewan 《统计学通讯:理论与方法》2013,42(23):5766-5776
AbstractCompeting risks data with current status censoring arise frequently from transversal studies in demography, epidemiology and reliability theory; where the only information about lifetime is whether the event of interest has occurred or not before a monitoring time. In practice, the monitoring times are discrete, but most of the studies consider them as continuous in nature. In the present paper, we propose a non parametric test for comparing cumulative incidence functions of current status competing risks data while the observation (monitoring) times are discrete. Asymptotic distribution of the test statistic is also derived. A simulation study is conducted to assess the finite sample behavior of the test statistic. The practical utility of the procedure is well demonstrated using a real-life data set on menopausal history of 2423 women given in Jewell, van der Laan, and Henneman (2003). 相似文献
18.
In this article, several methods to make inferences about the parameters of a finite mixture of distributions in the context of centrally censored data with partial identification are revised. These methods are an adaptation of the work in Contreras-Cristán, Gutiérrez-Peña, and O'Reilly (2003) in the case of right censoring. The first method focuses on an asymptotic approximation to a suitably simplified likelihood using some latent quantities; the second method is based on the expectation-maximization (EM) algorithm. Both methods make explicit use of latent variables and provide computationally efficient procedures compared to non-Bayesian methods that deal directly with the full likelihood of the mixture appealing to its asymptotic approximation. The third method, from a Bayesian perspective, uses data augmentation to work with an uncensored sample. This last method is related to a recently proposed Bayesian method in Baker, Mengersen, and Davis (2005). Our proposal of the three adapted methods is shown to provide similar inferential answers, thus offering alternative analyses. 相似文献
19.
In this article, we consider the progressive Type II right censored sample from Pareto distribution. We introduce a new approach for constructing the simultaneous confidence interval of the unknown parameters of this distribution under progressive censoring. A Monte Carlo study is also presented for illustration. It is shown that this confidence region has a smaller area than that introduced by Ku? and Kaya (2007). 相似文献
20.
In some survival studies, the exact time of the event of interest is unknown, but the event is known to have occurred during a particular period of time (interval-censored data). If the diagnostic tool used to detect the event of interest is not perfectly sensitive and specific, outcomes may be mismeasured; a healthy subject may be diagnosed as sick and a sick one may be diagnosed as healthy. In such cases, traditional survival analysis methods produce biased estimates for the time-to-failure distribution parameters (Paggiaro and Torelli 2004). In this context, we developed a parametric model that incorporates sensitivity and specificity into a grouped survival data analysis (a case of interval-censored data in which all subjects are tested at the same predetermined time points). Inferential aspects and properties of the methodology, such as the likelihood function and identifiability, are discussed in this article. Assuming known and non differential misclassification, Monte Carlo simulations showed that the proposed model performed well in the case of mismeasured outcomes; the estimates of the relative bias of the model were lower than those provided by the naive method that assumes perfect sensitivity and specificity. The proposed methodology is illustrated by a study related to mango tree lifetimes. 相似文献