On semiparametric random censorship models

Dikta, Gerhard

doi:10.1016/s0378-3758(97)00091-8

Cited by 77 publications

(71 citation statements)

References 8 publications

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“…An alternative approach, pursued in this paper, is based on a semiparametric adjustment to the nonparametric likelihood combined with Dikta's (1998) SRCMs-based estimator of S i (t). To explain the rationale for advocating SRCMs, note that under independence of the event and censoring times, the conditional probability m i (t) (see Sect.…”

Section: Introductionmentioning

confidence: 99%

Semiparametric simultaneous confidence bands for the difference of survival functions

Ahmed

Subramanian

2015

Lifetime Data Anal

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In the analysis of censored survival data, simultaneous confidence bands are useful devices to help determine the efficacy of a treatment over a control. Semiparametric confidence bands are developed for the difference of two survival curves using empirical likelihood and compared with the nonparametric counterpart. Simulation studies are presented to show that the proposed semiparametric approach is superior, with the new confidence bands giving empirical coverage closer to the nominal level. Further comparisons reveal that the semiparametric confidence bands are tighter and, hence, more informative. For censoring rates between 10 and 40 %, the semiparametric confidence bands provide a relative reduction in enclosed area amounting to between 2 and 10 % over their nonparametric bands, with increased reduction attained for higher censoring rates. The methods are illustrated using an University of Massachusetts AIDS data set.

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Section: Introductionmentioning

confidence: 99%

Semiparametric simultaneous confidence bands for the difference of survival functions

Ahmed

Subramanian

2015

Lifetime Data Anal

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“…Estimation of S and Λ with a logistic fit of p has been studied by Dikta (1998Dikta ( , 2000Dikta ( , 2001. It is shown in Dikta (1998) that, when the parametric model assumed for p is correct, this semiparametric estimator of S is at least as efficient as the KM estimator in terms of the asymptotic variance.…”

Section: Introductionmentioning

confidence: 99%

“…It is shown in Dikta (1998) that, when the parametric model assumed for p is correct, this semiparametric estimator of S is at least as efficient as the KM estimator in terms of the asymptotic variance. As a drawback, there is a clear risk of a miss-specification of the parametric model for p.…”

Section: Introductionmentioning

confidence: 99%

survPresmooth: AnRPackage for Presmoothed Estimation in Survival Analysis

López-de-Ullibarri¹,

Jácome²

2013

J. Stat. Soft.

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The survPresmooth package for R implements nonparametric presmoothed estimators of the main functions studied in survival analysis (survival, density, hazard and cumulative hazard functions). Presmoothed versions of the classical nonparametric estimators have been shown to increase efficiency if the presmoothing bandwidth is suitably chosen. The survPresmooth package provides plug-in and bootstrap bandwidth selectors, also allowing the possibility of using fixed bandwidths.

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“…We will refer to Ŝ D (t) as a Dikta-type estimator (Dikta 1998) and Ŝ I (t) as an inverse probability weighted (IPW) estimator (Robins and Rotnitzky 1992).…”

Section: Introductionmentioning

confidence: 99%

The missing censoring indicator model and the smoothed bootstrap

Subramanian¹,

Bean²

2008

Computational Statistics & Data Analysis

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For right censored data with missing censoring indicators, sub-density function kernel estimators play a significant role for estimating a survival function. Data-driven bandwidths for computing these kernel estimators are proposed. The bandwidths are obtained as minimizers of certain estimates of the mean integrated squared error (MISE). It is shown that the smoothed bootstrap offers a motivation for choosing the proposed MISE estimates for minimization. The efficacy of the proposed procedures is investigated through simulation studies and some illustrations are provided.

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On semiparametric random censorship models

Cited by 77 publications

References 8 publications

Semiparametric simultaneous confidence bands for the difference of survival functions

Semiparametric simultaneous confidence bands for the difference of survival functions

survPresmooth: AnRPackage for Presmoothed Estimation in Survival Analysis

The missing censoring indicator model and the smoothed bootstrap

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