Confidence Intervals for the Ratios of Ranked Scale Parameters for Censored Data

2003 ◽  
Vol 23 (3-4) ◽  
pp. 323-345 ◽  
Author(s):  
Parminder Singh ◽  
Amar Nath Gill
Keyword(s):  
Confidence Intervals ◽  
Censored Data ◽  
Scale Parameters

Influence function-based empirical likelihood for inference of quantile medical costs with censored data

2019 ◽  
Vol 29 (7) ◽  
pp. 1913-1934
Author(s):  
Jenny Jeyarajah ◽  
Guanhao Wei ◽  
Gengsheng Qin
Keyword(s):  
Confidence Intervals ◽  
Censored Data ◽  
Empirical Likelihood ◽  
Influence Function ◽  
Likelihood Ratio Statistic ◽  
Medical Costs ◽  
Finite Sample ◽  
Chi Square ◽  
Coverage Probabilities ◽  
Interval Lengths

In this paper, we propose empirical likelihood methods based on influence function and Jackknife techniques to construct confidence intervals for quantile medical costs with censored data. We show that the influence function-based empirical log-likelihood ratio statistic for the quantile medical cost has a standard Chi-square distribution as its asymptotic distribution. Simulation studies are conducted to compare coverage probabilities and interval lengths of the proposed empirical likelihood confidence intervals with the existing normal approximation-based confidence intervals for quantile medical costs. The proposed methods are observed to have better finite-sample performances than existing methods. The new methods are also illustrated through a real example.

scholarly journals Interval Estimation for Extreme Value Parameter with Censored Data

2011 ◽  
Vol 2011 ◽  
pp. 1-12
Author(s):  
Eun-Joo Lee ◽  
Dane Walker ◽  
David Elliott ◽  
Katlyn Mathy ◽  
Seung-Hwan Lee
Keyword(s):  
Weibull Distribution ◽  
Censored Data ◽  
Interval Estimation ◽  
Extreme Value Distribution ◽  
Extreme Value ◽  
Value Distribution ◽  
Finite Sample ◽  
Real World Data ◽  
Scale Parameters ◽  
Statistical Inferences

The Weibull distribution is widely used in the parametric analysis of lifetime data. In place of the Weibull distribution, it is often more convenient to work with the equivalent extreme value distribution, which is the logarithm of the Weibull distribution. The main advantage in working with the extreme value distribution is that unlike the Weibull distribution, the extreme value distribution has location and scale parameters. This paper is devoted to a discussion of statistical inferences for the extreme value distribution with censored data. Numerical simulations are performed to examine the finite sample behaviors of the estimators of the parameters. These procedures are then applied to real-world data.

scholarly journals An asymptotic measure of accuracy effect from censorship in parametric estimation

2003 ◽  
Vol 34 (2) ◽  
pp. 189-195
Author(s):  
Chung-Siung Kao
Keyword(s):  
Censored Data ◽  
Parametric Estimation ◽  
Scale Parameters ◽  
Data Value

An asymptotic measure is provided to evaluate the effect on loss of accuracy for censored data in parametric estimation of location and scale parameters. With this measure, it is shown that the amount of effect from censored data relative to noncensored data is invariant of the actual values of the location and scale parameters, but is only dependent on the form of underlying distributions which the data are originated. In addition, among the most well-known distributions, obtained results for the measure show that two censored data values together usually may possess more information than one noncensored data value in the parametric estimation for location and scale parameters.

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